Yashodha Bhavnani, Head of AI at Box, reveals Box's vision for intelligent content management that transforms unstructured data into actionable insights.

Topics Include:

• Yashodha Bhavnani leads AI products at Box.
• Box's mission: power how the world works together.
• Box serves customers globally across various industries.
• Works with majority of Fortune 500 companies.
• AI agents will join workforce for repetitive tasks.
• Workflows like hiring will become easily automated with AI.
• Content will work for users, not vice versa.
• Customers demand better experiences with generative AI.
• Box calls this shift "intelligent content management."
• 90% of enterprise content is unstructured data.
• AI thrives on unstructured data.
• Current content systems are unproductive and unsecured.
• AI can generate insights from scattered company knowledge.
• AI extracts metadata automatically from documents like contracts.
• Automated workflows triggered by AI-extracted data.
• Box provides enterprise-grade AI connected to your content.
• AI follows same permissions as the content itself.
• Customer data never used to train AI models.
• AI helps classify sensitive data to prevent leaks.
• Box offers choice of AI models to customers.
• AI is seamlessly connected with customer content.
• Administrators control AI deployment across their organization.
• Partnership with AWS Bedrock brings frontier models to Box.
• Box supports customers using their own custom models.
• Box preparing for AI agents to join workforce.
• Introduced "AI Units" for flexible pricing.
• Basic AI included free with Business Plus tiers.
• Both horizontal and vertical multi-agent architectures planned.
• Working toward agent-to-agent communication protocols.

Participants:

• Yashodha Bhavnani - VP of Product Management, AI products, Box

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Tech leaders from RingCentral, Zoom and AWS discuss how generative AI is transforming business communications while balancing challenges & regulatory concerns in this rapidly evolving landscape.

Topics Include:

• Introduction of panel on generative AI's impact on businesses.
• How to transition AI from prototypes to production.
• Understanding value creation for customers through AI.
• Introduction of Khurram Tajji from RingCentral.
• Introduction of Brendan Ittleson from Zoom.
• How generative AI fits into Zoom's product offerings.
• Zoom's AI companion available to all paid customers.
• Zoom's federated approach to AI model selection.
• RingCentral's new AI Receptionist (AIR) launch.
• How AIR routes calls using generative AI capabilities.
• AI improving customer experience through sentiment analysis.
• The disproportionate value of real-time AI assistance.
• Economics of delivering real-time AI capabilities.
• Real-time AI compliance monitoring in banking.
• Value of preventing regulatory fines through AI.
• Voice cloning detection through AI security.
• Democratizing AI access across Zoom's platform.
• Monetizing specialized AI solutions for business value.
• Challenges in taking AI prototypes to production.
• Importance of selecting the right AI models.
• Privacy considerations when training AI models.
• Maintaining quality without using customer data for training.
• Co-innovation with customers during product development.
• Scaling challenges for AI businesses.
• Case study of AI in legal case assessment.
• Ensuring unit economics work before scaling AI applications.
• Zoom's approach to scaling AI across products.
• Importance of centralizing but federating AI capabilities.
• Breaking down data silos for effective AI context.
• Navigating evolving regulations around AI.
• EU AI Act restrictions on emotion inference.
• Balancing regulations with customer experience needs.
• Future of AI agents interacting with other agents.
• How AI enhances human connection by handling routine tasks.
• Impact of AI on company valuations and M&A activity.

Participants:

• Khurram Tajji – Group CMO & Partnerships, RingCentral
• Brendan Ittleson – Chief Ecosystem Officer, Zoom
• Sirish Chandrasekaran – VP of Analytics, AWS

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Box's Chief Product Officer Diego Dugatkin discusses how the enterprise content management platform is leveraging AI through partnerships with AWS Bedrock and continuing to innovate for their customers.

Topics Include:

• Introduction of Diego Dugatkin as Box's Chief Product Officer
• Box provides cloud content management for enterprise customers
• Focus on Intelligent Content Management
• Box serves 115,000 customers including 70% of Fortune 500
• Company manages approximately one exabyte of enterprise data
• Box expanding product portfolio to offer more customer value
• Partnership with AWS Bedrock for AI implementation announced
• Collaboration with Anthropic for LLM technology integration
• Box offers neutral approach letting customers choose preferred LLMs
• Common misconceptions about generative AI capabilities and limitations
• Generative AI helps accelerate contract analysis and classification processes
• Box Hubs enables content curation and multi-document queries
• Success measured through hub creation and query accuracy metrics
• Long-term AWS partnership continues expanding with new technologies
• Amazon is major Box customer while Box uses AWS
• API integration important for third-party developer implementations
• AI development exceeding speed expectations in efficiency improvements
• Challenges remain in defining AI agent roles and capabilities
• Content strategy crucial for deploying intelligent content management
• Companies must prepare for AI agents in workplace
• Flexibility in tech stack recommended over single-vendor approach
• Next 12-24 months will see accelerated industry changes
• Box maintains innovative culture through intrapreneurship approach
• Company regularly hosts internal and external hackathons
• Focus on maintaining integrated platform while acquiring companies
• Partnership between Box and AWS continues growing stronger

Participants:

• Diego Dugatkin – Chief Product Officer, Box

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Through case studies of Graviton implementation and GPU integration, Justin Fitzhugh, Snowflake’s VP of Engineering, demonstrates how cloud-native architecture combined with strategic partnerships can drive technical innovation and build business value.

Topics Include:

• Cloud engineering and AWS partnership
• Traditional databases had fixed hardware ratios for compute/storage
• Snowflake built cloud-native with separated storage and compute
• Company has never owned physical infrastructure
• Applications must be cloud-optimized to leverage elastic scaling
• Snowflake uses credit system for customer billing
• Credits loosely based on compute resources provided
• Company maintains cloud-agnostic approach across providers
• Initially aimed for identical pricing across cloud providers
• Now allows price variation while maintaining consistent experience
• Consumption-based revenue model ties to actual usage
• Performance improvements can actually decrease revenue
• Company tracked ARM's move to data centers
• Initially skeptical of Graviton performance claims
• Porting to ARM required complete pipeline reconstruction
• Discovered floating point rounding differences between architectures
• Amazon partnership crucial for library optimization
• Graviton migration took two years instead of one
• Achieved 25% performance gain with 20% cost reduction
• Team requested thousands of GPUs within two months
• GPU infrastructure was new territory for Snowflake
• Needed flexible pricing for uncertain future needs
• Signed three to five-year contracts with flexibility
• Team pivoted from building to fine-tuning models
• Partnership allowed adaptation to business changes
• Emphasizes importance of leveraging provider expertise
• Recommends early engagement with cloud providers
• Build relationships before infrastructure needs arise
• Maintain personal connections with provider executives

Participants:

• Justin Fitzhugh – VP of Engineering, Snowflake

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In this AWS panel discussion, Naveen Rao, VP of AI of Databricks and Vijay Karunamurthy, Field CTO of Scale AI share practical insights on implementing generative AI in enterprises, leveraging private data effectively, and building reliable production systems.

Topics Include:

• Sherry Marcus introduces panel discussion on generative AI adoption
• Scale AI helps make AI models more reliable
• Databricks focuses on customizing AI with company data
• Companies often stressed about where to start with AI
• Board-level pressure driving many enterprise AI initiatives
• Start by defining specific goals and success metrics
• Build evaluations first before implementing AI solutions
• Avoid rushing into demos without proper planning
• Enterprise data vastly exceeds public training data volume
• Customer support histories valuable for AI training
• Models learning to anticipate customer follow-up questions
• Production concerns: cost, latency, and accuracy trade-offs
• Good telemetry crucial for diagnosing AI application issues
• Speed matters more for prose, accuracy for legal documents
• Cost becomes important once systems begin scaling up
• Organizations struggle with poor quality existing data
• Privacy crucial when leveraging internal business data
• Role-based access control essential for regulated industries
• AI can help locate relevant data across legacy systems
• Models need organizational awareness to find data effectively
• Private data behind firewalls most valuable for AI
• Customization gives competitive advantage over generic models
• Current AI models primarily do flexible data recall
• Next few years: focus on deriving business value
• Future developments in causal inference expected post-5 years
• Complex multi-agent systems becoming more important
• Scale AI developing "humanity's last exam" evaluation metric
• Discussion of responsibility and liability in AI decisions
• Companies must stand behind their AI system outputs
• Existing compliance frameworks can be adapted for AI

Participants:

• Naveen Rao – VP of AI, Databricks
• Vijay Karunamurthy – Field CTO, Scale AI
• Sherry Marcus Ph.D. - Director, Applied Science, AWS

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Suresh Vasudevan, CEO of Sysdig, discusses the evolving challenges of cloud security incident response and the need for new approaches to mitigate organizational risk.

Topics Include:

• Cybersecurity regulations mandate incident response reporting.
• Challenges of cloud breach detection and response.
• Complex cloud attack patterns: reconnaissance, lateral movement, exploit.
• Rapid exploitation - minutes vs. days for on-prem.
• Importance of runtime, identity, and control plane monitoring.
• Limitations of EDR and SIEM tools for cloud.
• Coordinated incident response across security, DevOps, executives.
• Criticality of pre-defined incident response plans.
• Increased CISO personal liability risk and mitigation.
• Documenting security team's diligence to demonstrate due care.
• Establishing strong partnerships with legal and audit teams.
• Covering defensive steps in internal communications.
• Sysdig's cloud-native security approach and Falco project.
• Balancing prevention, detection, and response capabilities.
• Integrating security tooling with customer workflows and SOCs.
• Providing 24/7 monitoring and rapid response services.
• Correlating workload, identity, and control plane activities.
• Detecting unusual reconnaissance and lateral movement behaviors.
• Daisy-chaining events to identify potential compromise chains.
• Tracking historical identity activity patterns for anomaly detection.
• Aligning security with business impact assessment and reporting.
• Adapting SOC team skills for cloud-native environments.
• Resource and disruption cost concerns for cloud agents.
• Importance of "do no harm" philosophy for response.
• Enhancing existing security data sources with cloud context.
• Challenges of post-incident forensics vs. real-time response.
• Bridging security, DevOps, and executive domains.
• Establishing pre-approved incident response stakeholder roles.
• Maintaining documentation to demonstrate proper investigation.
• Evolving CISO role and personal liability considerations.
• Proactive management of cyber risk at board level.
• Developing strong general counsel and audit relationships.
• Transparency in internal communications to avoid discovery risks.
• Security teams as business partners, not just technicians.
• Sysdig's cloud security expertise and open-source contributions.

Participants:

·        Suresh Vasudevan – CEO, Sysdig

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From hard-coded credentials to boardroom buy-in, join four tech security leaders from Clumio, Mongo DB, Symphony and AWS, as they unpack how building the right security culture can be your organization's strongest defense against cyber threats.

Topics Include:

• Security culture is crucial for managing organizational cyber risk
• Good culture enables quick decision-making without constant expert consultation
• Many security incidents occur from well-meaning people getting duped
• Panel includes leaders from AWS, Symphony, MongoDB, and Clumio
• Measuring security culture requires both quantitative and qualitative metrics
• Board-level engagement indicates organizational security culture maturity
• Self-reporting of security incidents shows positive cultural development
• Security committees' participation helps measure cultural engagement
• Hard-coded credentials remain persistent problem across organizations
• Internal audits and risk committees strengthen security governance
• Public security incidents change board conversations about priorities
• Leadership vulnerability and transparency help build trust
• Being pragmatic beats emotional responses in security leadership
• Security programs should align with business revenue goals
• Customer security requirements drive program improvements
• Excessive security questionnaires drain resources from actual security
• Security culture started as exclusionary, evolved toward collaboration
• Financial institutions often create unnecessary compliance burden
• Early security involvement in product development prevents delays
• Security teams must match development team speed
• Trust between security and development teams enables efficiency
• Small security teams can support large enterprise requirements
• Vendor partnerships help scale security capabilities
• Process changes work better than adding security tools
• Security leaders need deep business knowledge
• Technical depth and breadth remain essential skills
• Evangelism capability critical for security leadership success
• Influencing without authority key for security effectiveness
• Crisis moments create opportunities for security improvement
• Socializing between security and development teams builds trust
• DEF CON attendance helps developers understand security perspective
• Bug bounty programs provide continuous security feedback
• Regular informal meetings between teams improve collaboration
• Building personal relationships improves security outcomes
• Modern security leadership requires balance of IQ and EQ

Participants:

• Jacob Berry – Head of Information Security, Clumio
• George Gerchow – Interim CISO, Head of Trust, Mongo DB
• Brad Levy – Chief Executive Officer, Symphony
• Brendan Staveley – Global Sales Leader, Security Services, Amazon Web Services

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

AWS executive Giancarlo Casella explains how organizations can navigate global privacy regulations and achieve compliant international expansion using AWS's privacy reference architecture.

Topics Include:

• Welcome to executive forum on security and Gen AI
• Introduction of Giancarlo Casella from AWS Security Assurance Services
• AWS helps organizations with compliance and audit readiness
• Global expansion requires understanding local privacy laws
• Germany and France interpret GDPR differently
• Germany has Federal Data Protection Act (BDSG)
• France focuses on consumer privacy through CENIL
• Risk of non-compliance includes fines and reputation damage
• Privacy laws existed in only 10 countries in 2000
• EU Privacy Directive of 1990 was prominent
• By 2010, forty countries had privacy laws
• HIPAA and GLBA introduced in United States
• Now over 150 countries have privacy regulations
• 75% of world population under privacy laws soon
• Regulations are vague and open to interpretation
• GDPR example: encryption requirements lack specificity
• Need right stakeholders for privacy compliance
• Legal team must lead privacy interpretation
• Engineering implements technical privacy aspects
• Risk and compliance teams coordinate evidence gathering
• Data Protection Officer oversees entire program
• CIO, CTO, CISO alignment creates strong foundation
• Security transforms from bureaucratic to revenue enabler
• AWS develops cloud-specific privacy reference architecture
• Industry standards provide guidance frameworks
• AWS privacy reference architecture focuses on cloud specifics
• Data minimization and individual autonomy are key
• Case study: Middle Eastern AI company expands to Canada
• Company used CCTV at gas stations
• Created privacy baseline and roadmap
• Data flow documentation essential for compliance
• Continuous compliance strategy helps enable success
• Aligning stakeholders across different organizational lines
• Future of US federal privacy regulation discussed
• Discussion of responsible AI usage requirements

Participants:

• Giancarlo Casella - Head of Business Development and Growth Strategies, AWS Security Assurance Services

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Haggai Polak – Chief Product Officer, Securonix and a veteran cybersecurity expert examines how artificial intelligence, quantum computing, and resource constraints are fundamentally transforming the threat landscape for security leaders

Topics Include:

• AI transformation of cybersecurity landscape from past tactical focus
• CISO accountability and regulatory pressures increasing significantly
• Attack surface expanding beyond traditional network boundaries
• Quantum computing threatens current cryptographic protections
• Defenders remain understaffed and outmatched against sophisticated threats
• Securonix leads SIEM/SOAR space with 1000+ global customers
• World Economic Forum identifies misinformation/disinformation as major crisis
• AI benefits attackers more than defenders currently
• Small/medium enterprises falling below cyber poverty line
• AI enables faster, more sophisticated malware development
• Deepfakes caused $25M loss in Hong Kong CFO impersonation
• Digital tsunami: broadband, IoT, cloud everywhere expanding attack surface
• 50+ democracies face election security challenges in 2024
• Cloud intrusions increased 75% between 2022-2023
• Quantum-resistant cryptography transition needed within 10 years
• SEC regulations require specific cybersecurity incident disclosure guidelines
• 4 million unfilled cybersecurity positions globally
• Cybercrime-as-a-Service growing, estimated $1.6B annual revenue
• 81% of organizations faced ransomware attacks in 2023
• Insider threats increasing with remote work adoption
• 30,000+ vulnerabilities published last year, half critical/high
• Mean time to exploit now 44 days
• Securonix Eon leverages AI to increase analyst efficiency
• Dark web selling corporate credentials for $10,000
• Balance needed between protection and detection/response investments

Participants:

• Haggai Polak – Chief Product Officer, Securonix

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Dr. Yanbing Li, Chief Product Officer at Datadog, outlines how the company has integrated AI and automation into its incident response framework, helping customers manage both traditional security challenges and emerging AI-specific risks.

Topics Include:

• Introduced talk about incident response and CISO liability
• Datadog founded 14 years ago for cloud-based development
• Platform unifies observability and security for cloud applications
• Current environment has too many fragmented security products
• SEC requires material incident reporting within four days
• Datadog's incident response automates Slack room creation
• Response team includes Legal, Security, Engineering, and Product
• System tracks non-material incidents to identify concerning patterns
• Real-time telemetry data drives incident management automation
• On-call capabilities manage escalation workflows
• Datadog uses own products internally for incident response
• Company focuses on reducing time to incident detection
• AI brings new risks: hallucination, data leaks, design exploitation
• Bits.ai launched as LLM-based incident management co-pilot
• Tool synthesizes events and generates incident summaries
• Bits.ai suggests code remediation and creates synthetic tests
• Security built into AI products from initial design
• Prompt injection prevented through structured validation approach
• Sensitive data anonymized before LLM processing
• Engineering and security teams collaborate closely on AI
• LLM observability becoming critical for production deployments
• Customers need monitoring for hallucinations and token usage
• Datadog extends infrastructure monitoring into security naturally
• Company maintains strong partnership with AWS
• Q&A covered Bits.ai proactive capabilities and enterprise differentiation

Participants:

Yanbing Li – Chief Product Officer - Datadog

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Sanjay Kalra of Zscaler and Randy DeFauw of Amazon Web Services explore the hidden dangers of generative AI security—from invisible text manipulation and deep fakes to data poisoning and dark AI models—while offering practical strategies for protecting your enterprise in this era of generative AI.

Topics Include:

• AI security threats grouped into data, malicious use, trust/safety
• Data security critical for SaaS-based AI services
• Model training data vulnerable to poisoning and manipulation
• GenAI lacks traditional data deletion capabilities
• Access controls difficult once data becomes model embeddings
• Prompt injection attacks becoming widespread, with libraries available online
• Deepfake scams increasing in sophistication and frequency
• AI enhancing phishing attacks with better written content
• Dark AI models emerging specifically for malicious purposes
• Model hallucinations being exploited for security attacks
• AI accelerating analysis of stolen data
• Shadow AI usage by employees poses security risks
• Existing vendor AI integration creating unexpected security challenges
• Fine-grained access controls essential for AI applications
• PII protection critical in both inputs and outputs
• Comprehensive prompt and response logging necessary
• Invisible text manipulation emerging in resumes and RFPs
• Model fine-tuning can compromise built-in security guardrails
• Multi-language inputs create new security considerations
• Competition-sensitive content requires careful AI management
• AI firewalls needed for input/output monitoring
• Regular security testing required for AI models
• AI compliance standards emerging globally
• Multi-modal AI creating new security challenges
• Browser isolation helping control AI application usage

Participants:

• Sanjay Kalra – Product Management at Zscaler
• Randy DeFauw – Senior Principal Solutions Architect, Amazon Web Services

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This illuminating conversation with CyberArk's SVP of Finance, Nili Serr-Reuven, reveals how the 25-year-old cybersecurity leader successfully transformed from a traditional software company to a SaaS business model in just five quarters - far faster than the industry standard of 2-2.5 years - while maintaining strong margins and customer trust throughout the transition.

Topics Include:

• Introduction to SaaS transformation challenges and opportunities.
• Tomaz Perc introduces Nili Serr Reuven from CyberArk.
• Overview of CyberArk's 25-year history and milestones.
• Transition from a perpetual model to SaaS.
• CyberArk's accelerated transformation in just five quarters.
• Challenges of shifting from product-centric to customer-centric.
• Importance of market research and peer consultations.
• Key role of cross-functional collaboration in success.
• Explanation of "swallowing the fish" in SaaS.
• Managing short-term revenue drops during SaaS transformation.
• CyberArk's 70% SaaS revenue share post-transformation.
• Impact of global economic challenges on business strategy.
• CyberArk's robust demand for identity security solutions.
• Strategic leadership's role in transformation execution.
• CyberArk's disciplined financial planning during uncertainty.
• Establishing KPIs like ARR and customer satisfaction.
• Managing rising cloud costs with FinOps practices.
• CyberArk's approach to pricing and packaging SaaS solutions.
• Leveraging acquisitions to speed up SaaS capabilities.
• Impact of transformation on CyberArk's finance department.
• Evolution of finance roles to support SaaS growth.
• Communication with investors during transformative periods.
• The importance of cultural shifts in transformation success.
• Continuous learning, transparency, and collaboration as cornerstones.
• Advice for future SaaS leaders: plan, communicate, adapt.

Participants:

• Nili Serr Reuven – SVP Corporate Finance, CyberArk
• Tomaz Perc – SaaS Business Lead, Amazon Web Services

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

CEO Joe Kim shares how Sumo Logic has implemented generative AI to democratize data analytics, leveraging AWS Bedrock's multi-agent capabilities to dramatically improve accuracy.

Topics Include:

• Introduction of Joe Kim, CEO of Sumo Logic.
• Question: Overview of Sumo Logic's products and customers?
• Sumo Logic specializes in observability and security markets.
• Company leverages industry-leading log management and analytics capabilities.
• Question: How has generative AI entered this space?
• Kim's background is in product, strategy and engineering.
• Non-experts struggle to extract value from complex telemetry data.
• Generative AI provides easier interface for interacting with data.
• Question: How do you measure success of AI initiatives?
• Focus on customer problems, not retrofitting AI everywhere.
• Launched "Mo, the co-pilot" at AWS re:Invent.
• Mo enables natural language queries of complex data.
• Mo suggests visualizations and follow-up questions during incidents.
• Question: What challenges did you face implementing AI?
• Team knew competitors would eventually implement similar capabilities.
• Single model approach topped out at 80% accuracy.
• Multi-agent approach with AWS Bedrock achieved mid-90% accuracy.
• Bedrock offered security benefits and multiple model capabilities.
• Question: How was working with the AWS team?
• Partnered with Bedrock team and tribe.ai for implementation.
• Partners helped avoid pitfalls from thousands of prior projects.
• Question: What advice for other software leaders?
• Don't implement AI just to satisfy board pressure.
• Identify problems without mentioning generative AI first.
• Innovation should come from listening to customers.
• Question: Future plans with AWS partnership?
• Moving toward automated remediation beyond just analysis.
• Question: Has Sumo Logic monetized generative AI?
• Changed pricing from data ingestion to data usage.
• New model encourages more data sharing without cost barriers.

Participants:

• Joe Kim – Chief Executive Officer, Sumo Logic

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Soumya Banerjee, Associate Partner at McKinsey and Company, shares a comprehensive data-driven exploration of how generative AI is transforming the cybersecurity landscape, revealing emerging threats, organizational challenges, and strategic opportunities for security professionals.

Topics Include:

• AI's transformative potential in cybersecurity
• Survey of 500 cybersecurity professionals
• Generative AI's impact on security landscape
• Rising sophistication of phishing attacks
• Threat actors leveraging generative AI
• Deepfake technologies circumventing biometric controls
• Cybersecurity companies' valuation and growth
• Platform versus point solution debates
• Expanding cybersecurity attack surfaces
• Cloud security emerging as top priority
• AI use cases in threat detection
• Generative AI risks for organizations
• Securing AI investments and budgets
• Data protection and sensitive information challenges
• Regulatory scrutiny of AI technologies
• Talent gaps in cybersecurity sector
• Evolving cyber insurance risk models
• Identity and access management trends
• API and machine identity security
• LLM prompt and data protection
• Enterprise strategies for AI adoption
• Emerging technologies for cybersecurity defense
• Partnerships between cybersecurity vendors
• Disclosure risks in generative AI
• Future of cybersecurity technology landscape

Participants:

·        Soumya Banerjee – Associate Partner at McKinsey and Company

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Brendan Ittelson, Chief Ecosystem Officer of Zoom and Fedrico Torreti of AWS share how Zoom and AWS are leveraging generative AI to revolutionize application development, enhance cross-app personalization, and streamline user experiences with intelligent communication tools.

Topics Include:

• Introduction of speakers and session overview.
• Generative AI's disruptive impact across industries.
• Reimagining customer experiences with generative AI.
• Driving productivity through AI-powered applications.
• Challenges faced by application developers with AI integration.
• Importance of AI as a collaborator, not replacement.
• Cross-functional workplace complexity with multiple apps.
• Reducing task redundancy via generative AI automation.
• Case study: AI accelerating creative project briefings.
• Business outcomes achieved through thoughtful AI implementation.
• McKinsey and Gartner projections on generative AI's potential.
• Top use cases: R&D, customer operations, sales, marketing.
• Bridging data silos for richer user experiences.
• Security and compliance challenges in AI implementations.
• Zoom's federated model for adaptable AI architecture.
• Meeting summaries powered by Zoom AI Companion.
• Expanding generative AI into chat, whiteboards, voicemails.
• Vision for AI amplifying, simplifying, and delegating tasks.
• Integrating external data for personalized user experiences.
• Open platform approach for seamless data exchange.
• AI Companion empowering users with actionable insights.
• Role of AWS in enabling AI-first solutions.
• Addressing notification overload with smarter AI design.
• Enhancing end-to-end workflows with unified AI tools.
• Encouragement for developers to embrace thoughtful AI adoption.

Participants:

• Brendan Ittelson - Chief Ecosystem Officer, Zoom
• Fedrico Torreti - Head of Product, AppFabric, AWS

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Jonathan Shulman, Senior Partner at McKinsey & Company, highlights the transformative potential of AI in the software industry and the evolutions needed to capture emerging market opportunities.

Topics Include:

• AI's transformative potential in the software industry.
• Why AI is a massive business opportunity.
• Software industry evolution: Mainframe to Cloud SaaS eras.
• Potential entrance into a new AI-driven era.
• AI spend forecast: $15B to $200B by 2026.
• Most AI spend repurposed from existing IT budgets.
• Legacy software spend likely shifting towards AI.
• Importance of targeting specific, high-impact AI use cases.
• Key areas disrupted: sales, marketing, software engineering.
• AI's adoption rates vary by industry and function.
• Four waves of AI: predictive to agent-based.
• Most companies are still in early AI stages.
• Prioritize building agentic, end-to-end AI solutions.
• Winning companies invest disproportionately in AI innovation.
• Position offerings to tap into AI-specific budgets.
• Deliver complete workflows, not isolated point solutions.
• Generative AI accelerates development and iteration cycles.
• Scaling AI pilots remains a major industry challenge.
• Tool fragmentation undermines productivity and innovation.
• Change management critical for successful AI integration.
• Rethinking team roles and processes for AI deployment.
• Consumption-based pricing models gaining industry traction.
• Shift from perpetual to subscription to consumption models.
• Balancing value-driven and cost-efficient consumption pricing.
• AI market poised to redefine IT and business landscapes.

Participants:

• Jonathan Shulman – Senior Partner, McKinsey and Company

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AWS's Miguel Álava and BoardWave's Phill Robinson explore how European software companies can overcome market fragmentation, leverage cloud and generative AI, and adopt global strategies to scale competitively.

Topics Include:

• Introduction of Miguel Álava and Phill Robinson
• Overview of BoardWave's mission and community
• Challenges for European software companies in scaling globally
• Comparison of US and European software market dynamics
• Cloud adoption benefits for European software scalability
• Modern licensing models to centralize operations in Europe
• Impact of fragmented European markets on growth
• COVID-19's effect on sales strategies and efficiency
• Selling enterprise software across Europe via cloud tools
• Role of centralized marketing in global competitiveness
• Advantages of targeting the US before EMEA expansion
• BoardWave's "Voyager" model for scaling internationally
• Importance of solving universal versus local market problems
• Using cloud infrastructure to penetrate diverse markets
• Generative AI's role in product innovation and scaling
• Generative AI's transformational impact on global software industry
• European software companies' opportunity to lead in AI
• Building a collaborative European ecosystem for innovation
• Lessons from Silicon Valley's collaborative success model
• BoardWave's mentoring programs for European software CEOs
• AWS's support for cloud adoption and business scaling
• The evolving role of Chief Product Officers (CPOs)
• AI's potential to enhance cross-market product functionality
• Strategic next steps for scaling European software businesses
• Vision for Europe as a software superpower by 2034

Participants:

• Phill Robinson – Founder, Boardwave
• Miguel Alava – EMEA ISV General Manager, Amazon Web Services

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Richard Borstein of RingCentral and Richard Sonnenblick of Planview discuss how AI-driven innovations enhance customer and employee experiences, and unlock organizational growth through cutting-edge tools and strategies.

Topics Include:

• Importance of integrated communication tools for businesses.
• Challenges caused by disconnected communication platforms.
• Role of data in enhancing business operations.
• How RingCentral addresses communication and data integration issues.
• Benefits of real-time conversational intelligence in organizations.
• Leveraging AI to transform communication into actionable insights.
• Unlocking customer and employee voices through AI.
• How AI identifies patterns in customer interactions.
• Overview of RingSense for Sales AI tool.
• Real-world success story with RingSense for Sales.
• Streamlining customer interactions using AI-powered analysis.
• Enhancing employee productivity with AI-driven tools.
• AI solutions for faster, accurate information searches.
• Overview of RingCentral's Ring CX contact center solution.
• Improving customer satisfaction through AI-powered call analysis.
• Case study: Success with Ring CX at Worldwide Express.
• Features and benefits of RingCentral Events platform.
• Integrating event tech with existing customer workflows.
• Personalizing events with branding and engagement tools.
• PlanView’s use of AWS to drive innovation.
• Solving governance challenges with PlanView’s solutions.
• How generative AI accelerates productivity and decision-making.
• Making every user a power user with AI.
• Practical examples of generative AI in project management.
• Unlocking growth with next-gen AI-driven business tools.

Participants:

• Richard Bornstein - Chief Business Development Officer, RingCentral
• Richard Sonnenblick Ph.D – Chief Data Scientist, Planview

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Benjamin Flast, Director, Product Management at MongoDB discusses vector search capabilities, integration with AWS Bedrock, and its transformative role in enabling scalable, efficient, and AI-powered solutions.

Topics Include:

• Introduction to MongoDB's vector search and AWS Bedrock
• Core concepts of vectors and embeddings explained
• High-dimensional space and vector similarity overview
• Embedding model use in vector creation
• Importance of distance functions in vector relations
• Vector search uses k-nearest neighbor algorithm
• Euclidean, Cosine, and Dot Product similarity functions
• Applications for different similarity functions discussed
• Large language models and vector search explained
• Introduction to retrieval-augmented generation (RAG)
• Combining external data with LLMs in RAG
• MongoDB's document model for flexible data storage
• MongoDB Atlas platform capabilities overview
• Unified interface for MongoDB document model
• Approximate nearest neighbor search for efficiency
• Vector indexing in MongoDB for fast querying
• Search nodes for scalable vector search processing
• MongoDB AI integrations with third-party libraries
• Semantic caching for efficient response retrieval
• MongoDB's private link support on AWS Bedrock
• Future potential of vector search and RAG applications
• Example use case: Metaphor Data's data catalog
• Example use case: Okta's conversational interface
• Example use case: Delivery Hero product recommendations
• Final takeaways on MongoDB Atlas vector search

Participants:

• Benjamin Flast - Director, Product Management, MongoDB

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

David Gildea of Druva shares their approach to building cost-effective, fast generative AI applications, focusing on cybersecurity, data protection, and the innovative use of LLMs for simplified, natural language threat detection.

Topics Include:

• Introduction by Dave Gildea, VP of Product at Druva.
• Focus on building generative AI applications.
• Emphasis on cost and speed optimization.
• Mention of Amazon's Matt Wood keynote.
• AI experience with kids using "Party Rock."
• Prediction: GenAI as future workplace standard.
• Overview of Druva's data security platform.
• Three key Druva components: protection, response, and compliance.
• Druva's autonomous, rapid, and guaranteed recovery.
• Benefits of Druva’s 100% SaaS platform.
• Handling 7 billion backups annually.
• Managing 450 petabytes across 20 global regions.
• Druva’s high NPS score of 89.
• Introduction to Dru Investigate AI platform.
• Generative AI for cybersecurity and threat analysis.
• Support for backup and security admins.
• Simplified cybersecurity threat detection.
• AI-based natural language query interpretation.
• Historical analogy with Charles Babbage’s steam engine.
• "Fail upwards" model for LLM optimization.
• Using small models first, escalating to larger ones.
• API security and customer data protection.
• Amazon Bedrock and security guardrails.
• Testing LLMs with Amazon’s new prompt evaluation tool.
• Speculation on $100 billion future model costs.
• Session wrap up

Participants:

·        David Gildea - VP Product Generative AI, GM of CloudRanger, Druva

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Urmila Kukreja of Smartsheet and Nick Simha of AWS discuss leveraging Amazon Q’s Retrieval-Augmented Generation (RAG) solution to enhance productivity by enabling employees to quickly access relevant information within secure, integrated workflows like Slack, improving efficiency across the organization.

Topics Include:

• Introduction by Nick Simha, AWS.
• Overview of Amazon Q’s role in data analytics and Gen AI.
• Gen AI’s impact on productivity, ~30% improvement backed by Gartner study findings.
• General productivity improvement seen across various departments.
• Amazon Q’s developer code generation tool – rapid development
• Gen AI and LLMs’ challenges: security, privacy, and data relevance.
• Foundation models lack specific organizational knowledge by default.
• Empowering Gen AI to grant system access can cause issues
• Privacy concern: Sensitive data, like credit card info, can be central in data breaches
• Compliance is critical for organizational reputation and data integrity.
• Data integration techniques: prompt engineering, RAG, fine-tuning, custom training.
• RAG (Retrieval Augmented Generation) balances cost and accuracy effectively.
• Implementing RAG requires complex, resource-heavy integration steps.
• Amazon Q simplifies RAG integration with "RAG as a service."
• Amazon Q’s Gen AI stack overview, including Bedrock and model flexibility.
• Amazon Q connects to 40+ applications, including Salesforce and ServiceNow.
• Amazon Q respects existing security rules and data privacy constraints.
• Plugin functionality enables backend actions directly from Amazon Q.
• All configurations and permissions can be managed by administrators.
• Urmila Kukreja from Smartsheet explains real-world Q implementation.
• Smartsheet’s Ask Us Engineering Slack channel: origin of Q integration.
• Q integration in Slack simplifies data access and user workflow.
• "Ask Me" Slack bot lets employees query databases instantly.
• Adoption across departments is high due to integrated workflow.
• Future plans include adding data sources and personalized response features.
• Session wrap up

Participants:

• Urmila Kukreja – Director of Product Management, Smartsheet
• Nick Simha - Solutions Architecture Leader - Data, Analytics, GenAI and Emerging ISVs, AWS

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Harold Rivas – Chief Information Security Officer at Trellix, discusses the role of generative AI in cybersecurity, focusing on Trellix's adoption of AI for threat detection and model governance, while emphasizing the importance of privacy, responsible innovation, and cross-functional collaboration.

Topics Include:

• Introduction to generative AI and its impact on cybersecurity
• Harold’s background in financial services and cybersecurity roles
• Trellix’s focus on product feedback through the Customer Zero Program
• Overview of machine learning's role in anomaly detection at Trellix
• Development of guided investigations to assist security operations teams
• Generative AI's growing importance in cybersecurity at Trellix
• Launch of Trellix WISE at the RSA Conference in 2024
• Addressing the overload of security alerts with AI models
• Integration of various AI models like Mistral and Anthropic
• Reducing anomalies and workload for security operations teams
• Importance of privacy in generative AI adoption and data governance
• Challenges with GDPR and CPRA regulations in AI implementation
• Focus on privacy frameworks like the NIST Privacy Framework
• Need for multi-stakeholder involvement in AI governance
• Discussion on model governance inspired by financial services practices
• Importance of inventorying and testing AI models for security
• Benefits of an AI Center of Excellence (AICOE) within organizations
• Model governance in generative AI for regulatory and business outcomes
• The impact of AI on labor, jobs, and decision-making processes
• Addressing cyber risk and threat modeling in AI environments
• The double-edged sword of AI in offensive and defensive cybersecurity
• MITRE Atlas framework's role in AI-driven cybersecurity strategies
• Potential negative consequences. Auto dealership hacked – Chevy Tahoe sold for $1
• Importance of vulnerability management and developer training
• Evolution of AI security tools and responsible use of generative AI
• Collaboration, governance, and agility in AI adoption across organizations
• Q&A 1: Outcomes and responsibilities an generative AI COE should have?
• Q&A 2: Model governance and financial implications
• Q&A 3: CISO response to model development, compliance and learning with customer data
• Q&A 4: Thoughts and suggestions for rating systems for models
• Q&A 5: Selecting and evaluating models
• Q&A 6: Advice and experience for model deployment and technical controls
• Q&A 7: Human reviewing AI responses to ensure accuracy
• Q&A 8: Will AI help avoid major outages in the future?
• Q&A 9: How to test and see maturity of models?
• Session wrap up

Participants:

·        Harold Rivas – CISO at Trellix

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Executive leaders from Arctic Wolf, Docker and Illumio share insights on fostering a strong security culture, balancing innovation with security, and addressing challenges in data protection and AI model development.

Topics Include:

• Overview of security culture in different company teams
• Importance of guidelines and secure IT infrastructure for AI models
• Challenges of accessing customer data while maintaining security
• Need for anonymization in early AI model development
• Docker's open-source ecosystem and security integration
• Dogfooding own products to ensure product reliability and trustworthiness
• Illumio’s high customer trust and responsibility for strong security practices
• Balancing security awareness with development speed at Illumio
• Gamifying security training to increase awareness
• Interlocking with customers to enhance security understanding for developers
• Embedding security into the development process from the start
• Illumio's approach to security in agile, cloud-native development
• Adapting customer success strategies for evolving security needs
• Rise of non-developers using AI in enterprises
• Educating business leaders on security best practices
• Scaling customer enablement and education through community engagement
• Challenges of placing security responsibilities in the developer workflow
• Arctic Wolf’s AI strategy for secure development
• Use of anonymized data in secure AI model training
• Generative AI’s potential to augment human creativity and efficiency
• Panelists' views on private AI and segmented model development
• Measuring security culture progress with gamification and development metrics
• Addressing human factors in cybersecurity and social engineering threats
• Emphasizing resiliency and containment in preventing widespread cyberattacks.
• 
  

Participants:

• Dean Teffer – Vice President of Artificial Intelligence, Arctic Wolf
• Dixie Dunn – VP of Customer Success, Docker
• Mario Espinoza – Chief Product Officer, Illumio
• Brian Shadpour – General Manager, AWS

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

CTO Arun Kumar discusses how Socure leverages AWS and generative AI to collect billions of data points each day in order to combat sophisticated online fraud at scale.

Topics Include:

• Introduction of Arun Kumar, CTO of Socure
• What does Socure specialize in?
• KYC and anti-money laundering checks
• Mission: eliminate 100% fraud on the internet
• Fraud has increased since COVID
• Socure blocks fraud at entry point
• Works with top banks and government agencies
• CTO responsibilities include product and engineering
• Focus on increasing efficiency through technology
• Two goals: internal efficiency and combating fraud
• Countering tools like FraudGPT on dark web
• Measuring success through reduced human capital needs
• Fraud investigations reduced from hours to minutes
• Improved success rates in uncovering fraud rings
• Detecting multi-hop connections in fraud networks
• Question: Who's winning - fraudsters or AI?
• It's a constant "cat and mouse game"
• Creating a fraud "red team" similar to cybersecurity
• Partnership details with AWS
• Amazon Bedrock provides multiple LLM options
• Building world's largest identity graph with Neptune
• Real-time suspicious activity detection
• Blocking account takeovers through phone number changes
• Success story: detecting deepfake across 3,000 IDs
• Collecting hundreds of data points per identity
• Challenges: adding selfie checks and liveness detection
• Future strategy: 10x-100x performance improvements
• Creating second and third-order intelligence signals
• Internal efficiency applications of generative AI
• AI-powered sales tools and legal document review

Participants:

• Arun Kumar – Chief Technical Officer, Socure

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Hear the generative AI journeys of Cohere, Epiq, and Forcura, including their market assessments, use case prioritization, responses to ethical and security considerations, while discussing generative AI's impact on healthcare, legal industries, and business applications.

Topics Include:

• Panel Introductions by David Cristini
• Where is Focura at in their AI journey
• Summary of Epiq’s AI journey to date
• Cohere’s AI journey to date
• Where did each company begin and assessing the market opportunities
• Prioritizing of use cases for Epiq
• Focura’s quick focus and results with generative AI
• Simplifying healthcare and improving patient experience with generative AI
• How do experiments and proof of concepts develop into production?
• Indicators that Cohere uses to identify customers ready to move fast
• Usecases that allows Forcura customers to move forward
• Guidance on engaging the Executive Team – getting Executive alignment
• How are legal and healthcare customers responding to AI solutions and challenges
• Changes of priority from customer advisory panels
• Evolving questions and concerns of functionality and data
• Some customers reporting AI evaluation is slowing them down
• Usecases that are easier to start off with to gain trust and traction
• Dealing with AI concerns of ethics, security and privacy – managing objections
• Understanding ethics concerns – privacy can often be about where data resides
• Customers often want “traceability”
• Accuracy and reducing hallucinations – AI comes with risk, business have to decide on business risk
• Future facing – what are we excited about?
• Generative AI is excellent at translation services – ROI is excellent
• Business applications and social impact of generative AI

Participants:

• MaryAnn Wofford – VP of Sales, Cohere
• Paul O'Hagan - Senior Director Product Management – AI Platform, Epiq
• Annie Mueller Erstling – COO, Forcura
• David Cristini - Director, ISV Sales North America, AWS

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

J.B. Brown, VP of Engineering at Smartsheet, shares how integrating Amazon Q with Smartsheet's flexible work management platform has streamlined productivity and enhanced employee support through AI-driven automation.

Topics Include:

• Introduction by J.B. Brown, VP of Engineering at Smartsheet.
• Story about improving productivity
• Context about Smartsheet as an enterprise-scale work management platform.
• Examples of Smartsheet use in healthcare, TV streaming, and small businesses.
• Focus on not changing how companies work, offering flexibility.
• Integration with popular enterprise tech stack tools like Okta and Slack.
• Automations in Smartsheet for notifications and data synchronization.
• Smartsheet’s customer base includes large enterprises and small businesses.
• Overview of Smartsheet’s scale: 15 million users and $1 billion revenue.
• Smartsheet’s employee support system, including 270+ "Ask Us" Slack channels.
• Mention of AWS and the introduction of Amazon Q Business.
• Building a Smartsheet Q Business app for streamlined employee support.
• Setting up an Amazon Q Business app with proprietary data sources.
• Implementation of Slack integration for Smartsheet employee support.
• Example of AI summarizing Slack threads for improved efficiency.
• Demo of Amazon Q Business outperforming human experts in knowledge retrieval.
• Emphasizing the value of reducing response time and decision-making delays.
• Future development plans: Smartsheet-Amazon Q connector.
• Using AI to interrogate and manage Smartsheet project data.
• Invitation to AI-minded Smartsheet customers to test the new connector.

Participants:

• J.B. Brown - VP of Engineering at Smartsheet

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

AWS's Shahid Mohammed and Darktrace's Michael Beck discuss how generative AI innovations are transforming cybersecurity by both enhancing defences and introducing new, sophisticated threat management strategies.

Topics Include:

• Shahid Mohammed introduces himself as a lead solution architect at AWS.
• Mike Beck is Global Chief Information Security Officer at Darktrace.
• Darktrace specializes in AI-driven cybersecurity solutions for digital environments.
• Darktrace secures multiple digital data pots: email, network, cloud, SaaS, and endpoint.
• The conversation focuses on innovation in cybersecurity through AI.
• Mike emphasizes the benefits of Gen AI despite its security risks.
• Gen AI enables more complex, targeted attacks against organizations.
• Attackers use Gen AI to tailor attacks through phishing and deepfakes.
• Gen AI increases phishing complexity by eliminating common detection cues.
• Data privacy risks arise when large models process sensitive business data.
• Businesses must be mindful of AI’s impact on data sovereignty and security.
• Shahid compares the cybersecurity space to an arms race due to Gen AI.
• Mike stresses the importance of choosing the right AI for each task.
• Darktrace uses unsupervised machine learning and Gen AI together for defense.
• AI is essential for scaling cybersecurity efforts given today's threat complexity.
• Darktrace relies on AWS cloud for compute power, scaling, and innovation.
• AWS infrastructure helps accelerate Darktrace's R&D and operations securely.
• Security leaders should implement Gen AI policies and training.
• Mike advises technical controls and monitoring for safe Gen AI use.
• Gen AI is here to stay, but businesses must handle its security implications carefully.

Participants:

• Michael Beck – Global CISO - Darktrace
• Shahid Mohammed – Solution Architect Manager – Amazon Web Services

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Daryl Martis of Salesforce and Rashna Chadha of AWS share how Amazon Bedrock integrates with Salesforce to enhance AI applications, highlighting the partnership's strategic benefits, AI model customization, and secure deployment options.

Topics Include:

• Introduction to Amazon Bedrock and Salesforce partnership.
• Overview of Amazon Bedrock as an API-based generative AI service.
• The strategic collaboration between AWS and Salesforce.
• Salesforce Data Cloud and its integration with Amazon Bedrock.
• Overview of Salesforce Einstein and its use of Amazon SageMaker.
• Recent AI launches between Salesforce and AWS, including Slack AI and MuleSoft.
• Use cases of AI services like Amazon Textract within Salesforce.
• Bringing Your Own Large Language Model (BYO LLM) with Bedrock.
• Foundation models offered by Amazon Bedrock (Anthropic, Cohere, Llama).
• Overview of security, privacy, and compliance in Bedrock AI services.
• Salesforce Data Cloud’s unified customer data and real-time AI capabilities.
• Bedrock’s support for custom AI model evaluation and metrics.
• Consumption models in Bedrock: on-demand vs. provision throughput.
• Bedrock’s agent capabilities for real-world applications like scheduling.
• Demo of using Amazon Bedrock models within Salesforce.

Participants:

• Daryl Martis – Director of Product Management, Einstein AI - Salesforce
• Rashna Chadha – AI/ML Specialist – Principal Solution Architect – Amazon Web Services

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Ashish Arora, Head of Engineering & Machine Learning, Product Analytics at Autodesk, shares how personalized AI-powered experiences and real-time data can drive product adoption, featuring insights into Autodesk’s transformation journey, leveraging machine learning, and delivering actionable recommendations to millions of users.

Topics Include:

• Real-time data description and examples
• Leveraging AWS for real time and generative AI services
• Autodesk’s journey leveraging AWS to transform architecture and deliver personalized insights
• Overview of Autodesk and product portfolio
• Utilizing data gathered for customers
• Personalized data-driven insights for customers on Autocad and other products
• Descriptive insights: providing usage data for customers
• Prescriptive insights: Making recommendations to customers based on their workflows
• Predictive insights: Using ML to recommend products and features
• Autodesk processes 100+ billion events across all products, delivered 350+ million insights to customers, served to 3.5 million customers
• Example walkthrough – Rachael
• Architecture of Autodesk data and insight process
• Leveraging LLMs – Sagemaker and Bedrock
• Bringing it altogether
• Session wrap up

Participants:

• Ashish Arora – Head of Engineering & ML, Product Analytics - Autodesk
• Brian Slater – Principal Solutions Architect – Amazon Web Services

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

A panel discussion on presenting on security and data to Boards of Directors, focusing on metrics, ROI, generative AI, securing intellectual property, and strategic board engagement.

Topics Include:

• What security metrics are most valuable for Board of Directors
• Articulating ROI of security program
• Quantifying benefits of security program
• Sales enablement of the security team
• Driving efficiencies within the business with generative AI and more
• Quantifying business and template-based reporting to Boards with Diligent software
• Leveraging consultants and 3rd parties to leverage messages to Board of Directors
• Managing and communicating data posture and risk management
• Working with data leadership, securing intellectual property
• Challenges of labelling data
• Educating boards on software architecture principles and generative AI
• High focus and techniques for securing IP
• Enrolling Boards with generative AI use cases and innovation
• Creating communities of excellence
• Gamifying security and generative AI to increase internal knowledge
• Q&A 1: Taking action on a summarized document
• Q&A 2: Mental model for evaluative SaaS partners
• Q&A 3: Using the board to influence budgetary decisions
• Session wrap up

Participants:

• Satheesh Ravala - Chief Technology Officer, Diligent
• Josh Blackwelder – Deputy CISO, Sentinel One
• Robert Huber - Chief Security Officer, Head of Tenable Research, President Tenable Public
• Karen Henlsey - Principal WW Data & Generative AI Strategist, AWS

Lacework’s VP and Head of Engineering Arash Nikkar, and Product and Security Software Engineer Teddy Reed, discuss their work with generative AI and Amazon Bedrock, focusing on threat detection, chat interface improvements, and the rapid development of AI-driven solutions.

Topics Include:

• Introducing Lacework with Arash Nikkar
• Working with AWS and Bedrock
• Focusing on threat detection
• Lacework ingests over a trillion events each day
• Composite alerts for detecting anomalies
• Developing and improving the chat interface
• Teddy Reed talking chat interface improvements
• Reviewing the architecture
• Fast engagement with generative AI / AWS Bedrock
• The rapid delivery with Bedrock – took 20% of expected time
• Best practice – build in time to review and verify responses
• Measuring customer’s engagement and return frequency and feedback
• Understanding customer sentiment and topic analysis
• Achieving 60% completed results and feedback
• Transparency of source, response
• Enabling assistant to have more access to data from LLM
• Using AWS’ model evaluator, raising the accuracy scores
• Moving everything over to Bedrock for multiple reasons
• Familiarity of AWS tools helpful for all development and security teams
• Always challenging assumptions – is chat interface the right interface?
• Q&A 1: Using vector database for analysis, using results as system prompt
• Q&A 2: Approaching cost-optimization and balancing ROI
• Q&A 3: Using as automated remediation for findings
• Q&A 4: Data source Bedrock in leveraging

Session wrap up

Participants:

• Arash Nikkar – VP, Head of Engineering – Lacework
• Teddy Reed – Product and Security Software Engineer - Lacework

Massimo Ghislandi from AWS interviews Frank Contrepois, Chief Innovation Officer of Strategic Blue and Dvir Mizrahi, Head of FinOps for WIX sharing perspectives and best practices for FinOps, implementation, challenges and future FinOps trends for software companies.

Topics Include:

• FinOps is a new approach to managing cloud finances, bridging the gap between finance, engineering, and business stakeholders
• The implementation of FinOps can take a top-down or bottom-up approach, requiring collaboration and a common language across teams
• Shifting the conversation from "costs" to "investment" and "efficiency" has been an effective strategy for driving cultural change
• Focusing on automation, governance, remediation, and anomaly detection can have a greater impact than just cost observability
• Educating finance teams on technical cloud concepts and vice versa is crucial for building trust and alignment
• The future of FinOps may involve expanding beyond just cloud to encompass all IT assets and aligning with a company's overall values and business objectives
• Potential changes in legislation or accounting practices related to cloud could drastically impact the FinOps landscape

Participants:

• Frank Contrepois – Chief Innovation Officer, Strategic Blue
• Dvir Mizrahi – Head of Financial Engineering (FinOps), WIX
• Massimo Ghislandi – ISV Marketing Leader, EMEA, AWS

We feature a panel of executives from ASAPP, Glean, Smarsh, Socotra and AWS sharing essential strategies, including the role of Generative AI, trust-building, and addressing legal challenges to secure executive buy-in for transformative initiatives.

Topics Include:

• Introductions to panel
• Example of ideal Executive Seller
• Depth of business acumen and problem solving are important skills for Executive Sellers
• Framing a customer problem and create the argument
• Making selling to a C-Suite a team sport
• Keeping sellers and produce C-suite relevant
• Revolution and renaissance positioning
• Trust with the C-suite – do salesperson have a texting relationship w decision makers?
• How is Generative AI driving customer’s satisfaction and dissatisfaction?
• Data is the new oil
• Defining the business problem for insurance industry
• Helping customers reimagine business with Generative AI
• 80% of customers report the chatbot makes them mad
• The data journey is the precursor to the Generative AI journey
• The top unique legal challenges with Generative AI
• Legal now brought into early stage of sales process
• Turning legal concerns into an opportunity
• The book “Never Split the Difference” by Christopher Voss
• Calls to action from each panellist
• Session wrap-up

Participants:

• Daniel Rood – Senior Vice President Marketing, ASAPP
• AJ Tennant – Vice President Sales & Success, Glean
• Neva DePalma – General Council, Smarsh
• Ekine Akuiyibo – Chief Business Officer, Socotra
• Lauren Larscheid – Sr. Sales Leader, Business Applications, AWS

Today Anthropic’s Zach Witten takes us on a deep dive into Anthropic’s cutting-edge AI models—Claude Haiku, Sonnet, and Opus—exploring their safety-first approach to generative AI and sharing essential tips for prompt engineering.

Topics Include:

• Introductions, about Anthropic
• 3 models: Haiku, Sonnet and Opus
• Scaling laws for hardware, data and compute
• Competing to be safest AI solutions, safety-first organization
• Leader in jailbreak resistance
• Interpretability features and breakthroughs for AI models
• Basics of prompt engineering
• Improving prompts with Claude
• Details matter – small changes to spelling, context will greatly improve results
• System prompt – role setting will improve results (i.e. “You are an expert mathematician…” for math query
• Be clear and direct – use XML tags where possible
• Encourage Claude to think step-by-step – answering fast comes with accuracy risk
• Use examples to provide additional clarity to Claude
• Bonus tips for image-based prompt engineering
• Q&A 1) Who wrote the meta-prompts in the cookbook?
• Q&A 2) Guidance for writing prompts for prompt generator
• Q&A 3) Best practices for tabular and structured data
• Q&A 4) Maintaining “tone” across hundreds/thousands of responses
• Q&A 5) Reverse engineering a prompt

Oron Noah of Wiz outlines how organizations evolve their security practices to address new vulnerabilities in AI systems through improved visibility, risk assessment, and pipeline protection.

Topics Include:

• Introduction of Oron Noah, VP at Wiz.
• Wiz: largest private service security company.
• $1.9 billion raised from leading VCs.
• 45% of Fortune 100 use Wiz.
• Wiz scans 60+ Amazon native services.
• Cloud introduced visibility challenges.
• Cloud created risk prioritization issues.
• Security ownership shifted from CISOs to everyone.
• Wiz offers a unified security platform.
• Three pillars: Wiz Cloud, Code, and Defend.
• Wiz democratizes cloud security for all teams.
• Security Graph uses Amazon Neptune.
• Wiz has 150+ available integrations.
• Risk analysis connects to cloud environments.
• Wiz identifies critical attack paths.
• AI assists in security graph searches.
• AI helps with remediation scripts.
• AI introduces new security challenges.
• 70% of customers already use AI services.
• AI security requires visibility, risk assessment, pipeline protection.
• AI introduces risks like prompt injection.
• Data poisoning can manipulate AI results.
• Model vulnerabilities create attack vectors.
• AI Security Posture Management (ASPM) introduced.
• Four key questions for AI security.
• AI pipelines resemble traditional cloud infrastructure.
• Wiz researchers found real AI security vulnerabilities.
• Wiz AI ASPM provides agentless visibility.
• Supports major AI services (AWS, OpenAI, etc.).
• Built-in rules detect AI service misconfigurations.

Participants:

• Oron Noah – VP Product Extensibility & Partnerships, Wiz

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Today, Dr. Ratinder Paul Singh Ahuja of Pure Storage takes us through how his organization is leveraging Amazon Bedrock to enrich the digital experience for end users and increase returns for the company.

Topics Include:

• Introductions
• Generative AI activity within Pure Storage
• Ownership and expertise of team, role of generative AI
• Rapid changes require dedicated team reporting to office of CTO
• Where Pure Storage is investing – Productivity gains, Customer Experience, R&D
• Vision starts with the needs of the business users
• GenAI Ops – Content, Voctor databases for ingestion, query strategies & security
• Example – Purchase Acquisition Process
• Features for a mobile experience
• Configurations and logs are getting more enhanced with generative AI
• Defining schema and improving large language model for more accurate responses
• Security models and deployment
• Summary and session wrap up
• Q&A 1) How did the team get trained to use the generative AI tools and systems?
• Q&A 2) How did the team reduce the hallucinations?
• Q&A 3) How did you decide on which foundation models to use?
• Q&A 4) The ROI of this particular use case
• Q&A 5) Models working with poly-morphic evolving inputs
• Session conclusion

Federico Torreti and Tom Sly of AWS discuss how application developers can leverage Generative AI to enhance cross-app experiences, minimize custom integrations and increase the value-add of enhanced communication features.

Topics Include:

• Federico Torreti intro: What is AWS’ vision for applications
• Focus of Machine Learning & AI
• Ability to build rapid prototypes, experimentation
• Cambrian explosion of SaaS applications
• The challenge of toggling of multiple applications
• Bringing the world of disconnected apps
• Data and focusing on the primary value for customer
• Generating more content will raise number of alerts and potential of burnout
• Tom Sly intro: Being delighted by businesses
• Customers expect personalization from businesses
• More than 150,000 customers leverage AWS for communications strategy
• Leveraging messaging to increase customer delight
• 2 examples: restaurant and medical need
• Session wrap up

Participants:

• Federico Torreti – Head of Product – Amazon Q, Amazon Web Services
• Tom Sly - Director, Special Projects, Amazon Web Services

Sara Yamase, Partner at Simon-Kucher & Partners, Head of Software, Internet and Media Practice shares guidance and industry examples on generative AI pricing and GTM strategies.

Topics Include:

• What percentage of companies are developing Gen AI features for customers
• Projected returns on Gen AI investment
• Articulating the value is 1st step in building pricing and monetization strategy
• Almost half of VC funding in last 5 quarters were for AI solutions
• Getting through the hype cycle and trough of disillusionment
• Education, Marketing, Food industry examples of companies clarifying value of generative AI to customers
• Having strong data sets for identifying trends
• Pricing tenets for generative AI
• Indirect monetization – more usage, faster, greater productivity, etc
• Standalone Generative AI software with bespoke pricing
• Ability to scale pricing per customer usage
• Subscription selling for generative AI software
• Choosing pricing model for generative AI solutions
• Summaries and session wrap up

Today Nicole Eagan, Chief Strategy and AI Officer and Michael Beck, Global CISO of Darktrace AI Research centre share experience, predictions and guidance on the future of AI and Cybersecurity.

Topics Include:

• A brief history of Darktrace
• Applying AI to the challenge of cyber security
• Changes and evolution of cyber security threats
• What are the key security challenges business are facing?
• Generative AI provided a seismic shift with threat actors
• Best practices for managing and scaling security teams
• Guidance for leaders for baking AI into workflows
• Responsible AI best practices for building trust
• Trends of Generative AI on the security landscape
• Leveraging Generative AI to transform the customer experience
• Predictions for emerging technology trends over the next 10 years
• Recommendations and parting wisdom for security and AI
• Keeping a workforce trained and relevant for technology trends
• Interview wrap up

Participants:

• Nicole Eagan – Chief Strategy Officer and AI Officer, Darktrace
• Michael Beck – Global CISO, Darktrace
• Phil Le-Brun – Director, Enterprise Strategy, Amazon Web Services

A panel discussion with executives from ActionIQ, FloQast and Wiz on experiences and best practices for working and selling to customer C-suites.

Topics Include:

• Panel introductions
• Keeping products and sellers focused on C-Suite outcomes
• Customer C-suite focus, identifying internal champions
• Keeping sales motion concise for key C-Suite
• Connecting value for enterprise space
• Impact of Generative AI and inventing on behalf of customers
• Customer impressions of GenAI and going beyond the hype
• Helping customers reimagine / hack their business
• C-suite concerns about Generative AI
• Flipping objections into selling points for C-Suite
• Building confidence for security, data and GenAI for Executives
• Final thoughts, Session wrap-up
• 
  

Participants:

• Justin DeBrabant – Chief Product Officer, ActionIQ
• Stefan van Duyvendijk – Accounting Operations Evangelist, FloQast
• Rick Kickert – Senior Vice President of Revenue Growth & Strategy, Wiz
• Veronica McCarthy – Senior Sales Manager, ISV, Amazon Web Services

We feature a conversation with Yuelin (李玥琳)Li, Chief Product Officer of Onfido and Phil Le-Brun - Enterprise Strategist, Amazon Web Services, about the pivotal role of AI, machine learning, and generative AI in fraud prevention and security in the identity verification industry.

Topics Include:

• Yuelin Li career journey
• Overview and mission of Onfido
• Use of AI and Machine Learning at Onfido
• Successes in reducing fraud with identity verification
• Challenges faced and overcome with Machine Learning
• Secure rapid iteration and constant experimentation
• Working with customers in highly regulated industries
• Hot topics and ethics with Generative AI
• Training, managing bias and maintaining accuracy of models
• Staying aligned with customers
• Skillets required, creating development paths for staff
• Creating a culture of learning in the organisation
• Deciding how to place bets on technology advances
• What excites Yuelin Li most about Generative AI
• Advice for other companies setting out on a similar journey
• Session wrap-up

Executive Leaders from Proofpoint, Sumo Logic and Zendesk share their experiences and best practices for collaboration with AWS to deliver transformative impact to their business using Generative AI.

Panelists:

• Patrick Wheeler, Director, Product Management, Proofpoint
• Bashyam Anant, Senior Director, Product Management, Sumo Logic
• Patrick Copeland, Chief Engineering & Product Officer, Zendesk
• Olawale Oladehin, Director ISV Solutions Architecture, North America, AWS

Topics Include:

• Introductions of Panel
• Where each organization is doing with Generative AI
• Designing data strategy around business outcomes
• Making subject matter experts within the business
• Defining what success metrics and value to focus on
• Metrics and KPIs and framework for experiments
• Thinking and leveraging partnerships for Generative AI
• Developing skillsets, retraining teams and managing resources
• Lessons learned, what would you change, advice for others
• Session wrap-up

Jimmy Hillis, Head of Engineering at Airtable, shares examples, guidance and major themes for how businesses can successfully build and leverage AI within their enterprise applications and workflows.

Topics Include:

• Introductions and Airtable overview
• Challenges businesses have articulating how AI will add value
• Core insights: AI needs to leverage your own data
• AI functionality needs to live within existing tools and workflows
• Have workflow and business experts building prompts for the desired function
• AI presents a new set of fears and restrictions
• Examples for successful implementation of AI
• Airtable AI field examples and automations feature
• Example of leveraging technology to reduce manual activity
• Data governance, training data for use
• Network governance and Flexibility
• Recapping the themes, session wrap up

In this highly informative episode, we share strategies and best practices for driving growth for SaaS companies featuring Kulwinder Kalsi, head of UK and Ireland Enterprise Software and SaaS Architecture and Johan Broman, Head of Solutions Architecture for Independent Software Vendors for Europe, Middle East & Africa.

Topics Include:

• Discover the main expectations end customers have of SaaS companies, including frictionless tenant onboarding, instrumentation/monitoring, pricing transparency, and focusing on core innovation.
• Explore key trends shaping the SaaS industry, such as the shift towards consumption-based pricing models, complex pricing strategies that align packaging with customer segments, and leveraging other software partners to remove undifferentiated heavy lifting.
• Learn how AWS can help SaaS companies with its global infrastructure, robust security measures, and rich ecosystem of services and partners to accelerate growth and innovation.
• Get insights into monetizing data strategies that SaaS companies can adopt to unlock additional revenue streams from their tenant data.
• Understand the different ways AWS partners, including systems integrators, professional services, and other software vendors, can support SaaS companies through their journey.
• Receive practical advice on approaching cloud migration and modernization, including aligning leadership, assessing growth vs. retention goals, and choosing the right mix of lift-and-shift or full modernization.
• Gain a nuanced perspective on developing AI solutions, covering use case identification, model selection, deployment techniques like prompt engineering and fine-tuning, and the importance of monitoring and management.
• Hear expert tips on navigating the rapidly evolving generative AI landscape, leveraging AWS services like SageMaker and Bedrock, and utilizing specialized AI chips like Trainium and Inferentia.

Business applications are catalyzing profound transformations across industries, streamlining operations, enhancing productivity, and fostering innovation. Leveraging advanced technologies such as generative AI, these applications are reshaping traditional business models, driving agility, and fueling competitive advantage in the global marketplace.

Panelists:

• Neboysa Omcikus - Head of Strategy, https://www.linkedin.com/company/gleanwork/Glean
• Steve Antonakakis - Divisional COO, Enterprise Productivity, PDI Technologies
• Shiv Sehgal - Executive Vice President, Audience Analytics, RSG Media, a Naviga Global company
• Karen Hensley - Principal Data Strategist, AWS

Topics Include:

• Panel Introductions
• How did you decide where to focus with Generative AI?
• Quantifying the value of projects with customers
• Delivering the value and capability for customers
• Do customers care deeply about the technology or the experience?
• How did you move from “test and experiment” phase to production
• How did you reevaluate your data strategy when developing software?
• Working with customers on their data safety, security and ethics
• Driving innovation within data regulatory and compliance requirements
• Looking into the future – What’s the next wave of transformation for industry specific solutions?

Ruslan Kusov of SoftServe presents how their Application Modernization Framework accelerates ISV modernization, assesses legacy code, and delivers modernized applications through platform engineering principles.

Topics Include:

• Introduction of Ruslan Kusov, Cloud CoE Director at SoftServe
• SoftServe builds code for top ISVs
• Success case: accelerated security ISV modernization by six months
• Healthcare tech company assessment: 1.6 million code lines in weeks
• Business need: product development acceleration for competitive advantage
• Business need: intelligent operations automation
• Business need: ecosystem integration and "sizeification" to cloud
• Business need: secure and compliant solutions
• Business need: customer-centric platforms with personalized experiences
• Business need: AWS marketplace integration
• Distinguishing intentional from unintentional complexity
• Platform engineering concept introduction
• Self-service internal platforms for standardization
• Applying platform engineering across teams (GenAI, CSO, etc.)
• No one-size-fits-all approach to modernization
• SAMP/SEMP framework introduction
• Core components: EKS, ECS, or Lambda
• Modular structure with interchangeable components
• Case study: ISV switching from hardware to software products
• Four-week MVP instead of planned ten weeks
• Six-month full modernization versus planned twelve months
• Assessment phase importance for business case development
• Calculating cost of doing nothing during modernization decisions
• Healthcare customer case: 1.6 million code lines assessed
• Benefits: platform deployment in under 20 minutes
• Benefits: 5x reduced assessment time
• Benefits: 30% lower infrastructure costs
• Benefits: 20% increased development productivity with GenAI
• Integration with Amazon Q for developer productivity
• Closing Q&A on security modernization and ongoing management

Participants:

• Ruslan Kusov – Cloud CoE Director, Softserve

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Nicholas Marwell, Member of Technical Staff of Anthropic, shares predictions for Generative AI models as well as guidance on safely training and scaling them for the near future.

Topics Include:

• Where are Generative AI Models heading
• About Anthropic
• Claude Opus, Claude 3 Sonnet & Claude 3 Haiku
• Scaling laws impact on models
• Training models for text, images and multimedia
• AI Safety, high stakes and stewarding through potential dangers
• Constitutional AI and interpretability research
• Benefits of Features – combinations of neurons
• Final thoughts – high growth and pace for coming months and years

Daniele Di Mattia, Partner at McKinsey and Company and Miguel Alava, General Manager of AWS for software companies in EMEA, discuss strategic software industry insights and trends in Europe, Middle East, Africa and beyond that will shape the future of investment, product development as well as opportunities for regional and global expansion.

Topics include:

• Macro environment challenges and focus on cost optimization for software companies
• Generative AI's massive impact and expanding total addressable market
• The need for increased R&D investment in Europe, Middle East and Africa region
• Leveraging cloud elasticity and optimization for cost-conscious environments
• Impact of generative AI on product development and developer productivity
• Embedding generative AI in sales, marketing and customer operations
• Importance of data strategy and prioritizing high-value use cases
• Being bold and courageous in investing during technological inflection points
• Opportunities for software companies to lead in their respective market segments

Frank Della Rosa, Research Vice President of SaaS, Business Platforms, and Industry Cloud at IDC, shares the recent trends of the software industry and how some successful software companies are adapting their strategies to best take advantage and create value.

Topics Include:

• The worldwide forecast for SaaS and cloud software
• Major growth stats for SaaS and Cloud software
• North America growth deep dive
• Top businesses investing in generative AI
• Co-creation with individuals, teams and machines
• Criticality of roadmap for generative AI
• Monetizing generative AI’s impact on demand
• Data’s role in the “Year of the Platform”
• Purpose built platforms
• Enterprise generative AI use cases
• Opportunities and challenges of generative AI
• Informing ISV and SaaS partners on tech buyer focus
• Impact of software architecture from edge infrastructure
• Generative AI and application modernization services
• Enhanced productivity, operational excellence, Hyper personalization
• Domain specific models and vertical SaaS companies
• Where are we going? What’s ahead?
• Reiterating the final points

Mark Billige, CEO of global consultancy firm Simon Kucher and Miguel Alava, General Manager of AWS for software companies in EMEA, discuss strategic software industry insights and trends that will shape the future of data, generative AI and cost optimization.

Topics Include:

• Shift from Growth-at-All-Costs to Profitable Growth Models
• Monetizing the Value of Generative AI Offerings
• Treating Data as a Monetizable Asset for Software Companies
• Strategies for Expanding into the U.S. Software Market
• Rethinking Software Pricing and Revenue Models
• Organizational Changes Required for AI-Driven Innovation
• Avoiding Undervaluing Software Offerings and Leaving Money on the Table
• Balancing Cost Optimization with Investing in Growth
• Leveraging Partnerships/Acquisitions for New Market Entry