Jon Yoo, CEO of Suger, shares how his company automates the complex & challenging workflows of selling software through cloud marketplaces like AWS.

Topics Include:

• Jon Yoo is co-founder/CEO of Suger.
• Suger automates B2B marketplace workflows.
• Handles listing, contracts, offers, billing for marketplaces like AWS.
• Co-founder previously led Confluent's marketplace enablement product.
• Confluent had 40-50% revenue through cloud marketplaces.
• Required 10-20 engineers working solely on marketplace integration.
• Engineers prefer core product work over marketplace integration.
• Product/engineering leaders struggle with marketplace deployment requirements.
• Marketplace customers adopt without marketing, creating unexpected management needs.
• Version control is challenging for marketplace-deployed products.
• License management through marketplace creates engineering challenges.
• Suger helps sell, resell, co-sell through AWS Marketplace.
• Marketplace integration isn't one-time; requires ongoing maintenance.
• Business users constantly request marketplace automation features.
• Suger works with Snowflake, Intel, and AI startups.
• Data security concerns drive self-hosted AI deployments.
• AI products increasingly deploy via AMI/container solutions.
• AI products use usage-based pricing, not seat-based.
• Usage-based pricing creates complex billing challenges.
• AI products are tested at unprecedented rates.
• Two deployment options: vendor cloud or customer cloud.
• SaaS requires reporting usage to marketplace APIs.
• Customer-hosted deployment simplifies some billing aspects.
• Marketplaces need integration with ERP systems.
• Version control particularly challenging for AI products.
• Companies need automated updates for marketplace-deployed products.
• License management includes scaling up/down and expiration handling.
• Suger aims to integrate with GitHub for automatic updates.

Participants:

·        Jon Yoo – CEO and Co-founder, Suger

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

SentinelOne's Ric Smith shares how Purple AI, built on Amazon Bedrock, helps security teams handle increasing threat volumes while facing budget constraints and talent shortages.

Topics Include:

• Introduction of Ric Smith, President of Product Technology and Operations
• SentinelOne overview: cybersecurity company focused on endpoint and data security
• Customer range: small businesses to Fortune 10 companies
• Products protect endpoints, cloud environments, and provide enterprise observability
• Ric oversees 65% of company operations
• Purple AI launched on AWS Bedrock
• Purple AI helps security teams become more efficient and productive
• Security teams face budget constraints and talent shortages
• Purple AI helps teams manage increasing alert volumes
• Top security challenge: increased malware variants through AI
• AI enables more convincing spear-phishing attempts
• Identity breaches through social engineering are increasing
• Voice deepfakes used to bypass security protocols
• Future threats: autonomous AI agents conducting orchestrated attacks
• SentinelOne helps with productivity and advanced detection capabilities
• SentinelOne primarily deployed on AWS infrastructure
• Using SageMaker and Bedrock for AI capabilities
• Best practice: find partners for AI training and deployment
• Customer insight: Purple AI made teams more confident and creative
• AI frees security teams from constant anxiety
• SentinelOne's hyper-automation handles cascading remediation tasks
• Multiple operational modes: fully automated or human-in-the-loop
• Agent-to-agent interactions expected within 24 months
• Common misconception: generative AI is infallible
• AI helps with "blank slate problem" providing starting frameworks
• AI content still requires human personalization and review
• AWS partnership provides cost efficiency and governance benefits

Participants:

·        Ric Smith – President – Product, Technology and Operations, SentinelOne

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

Sam Gantner, Chief Product Officer of Nexthink, reveals how DEX is moving IT from reactive firefighting to proactive problem prevention and transforming enterprise productivity.

Topics Include:

• DEX stands for Digital Employee Experience
• DEX eliminates IT issues preventing employee productivity
• Shifts IT from reactive to proactive problem-solving
• Employees often serve as IT problem alerting systems
• Best IT is transparent to employees
• DEX solves device sluggishness and slow application issues
• Network problems consistently appear across organizations
• IT teams often lack visibility into employee experiences
• Many organizations waste money on unused software licenses
• DEX Score measures comprehensive employee IT experience
• Surveys capture subjective aspects of technology experience
• Reduction of actual problems differs from ticket reduction
• Nexthink uses lightweight agents on employee devices
• Browser monitoring essential as browsers become application platforms
• Employee engagement metrics capture real-time feedback
• Nexthink rebuilt as cloud-native platform using AWS services
• Company deploys across 10+ global AWS regions
• 30% of engineering resources dedicated to AI development
• One customer eliminated 50% of IT tickets
• Another recovered 37,000 productivity hours worth $3M annually
• A third saved $1.3M by identifying unused licenses
• AI implementation requires dedicated employee training
• Good AI now better than perfect AI never
• Technology adoption is the next DEX frontier
• Digital dexterity becoming critical for maximizing IT investments

Participants:

• Samuele Gantner – Chief Product Officer, Nexthink

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

Linda Ivy-Rosser, Vice President for Forrester, outlines the evolution of business applications and forward thinking predictions of their future.

Topics Include:

• Linda Ivy-Rosser has extensive business applications experience since the 1990s.
• Business applications historically seen as rigid and lethargic.
• 1990s: On-premise software with limited scale and flexibility.
• 2000s: SaaS emergence with Salesforce, AWS, and Azure.
• 2010s: Mobile-first applications focused on accessibility.
• Present: AI-driven applications characterize the "AI economy."
• Purpose of applications evolved from basic to complex capabilities.
• User expectations grew from friendly interfaces to intelligent systems.
• Four agreements: AI-infused, composable, cloud-native, ecosystem-driven.
• AI-infused: 69% consider essential/important in vendor selection.
• Composability expected to grow in importance with API architectures.
• Cloud-native: 79% view as foundation for digital transformation.
• Ecosystem-driven: 68% recognize importance of strategic alliances.
• Challenges: integration, interoperability, data accessibility, user adoption.
• 43% prioritizing cross-functional workflow and data accessibility capabilities.
• Tech convergence recycles as horizontal strategy for software companies.
• Data contextualization crucial for employee adoption of intelligent applications.
• Explainable AI necessary to build trust in recommendations.
• Case study: 83% of operators rejected AI recommendations without explanations.
• Tulip example demonstrated three of four agreements successfully.
• Software giants using strategic alliances as competitive advantage.
• AWS offers comprehensive AI infrastructure, platforms, models, and services.
• Salesforce created ecosystem both within and outside their platform.
• SaaS marketplaces bridge AI model providers and businesses.
• Innovation requires partnerships between software vendors and ISVs.
• Enterprises forming cohorts with startups to solve business challenges.
• Software supply chain transparency increasingly important.
• Government sector slower to adopt cloud and AI technologies.
• Change resistance remains significant challenge for adoption.
• 69% prioritize improving innovation capability over next year.

Participants:

• Linda Ivy-Rosser - Vice President, Enterprise Software, IT services and Digital Transformation Executive Portfolio, Forrester

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

New Relic's Chief Customer Officer Arnaldo (Arnie) Lopez details how their observability platform helps 70,000+ customers monitor cloud performance through AWS infrastructure while introducing AI capabilities that simplify operations.

Topics Include:

• Arnie Lopez is SVP, Chief Customer Officer at New Relic.
• Oversees pre-sales, post-sales, technical support, and enablement teams.
• New Relic University offers customer certifications.
• Founded in 2008, pioneered application performance monitoring (APM).
• Now offers "Observability 3.0" for full-stack visibility.
• Prevents interruptions during cloud migration and operations.
• Serves 70,000+ customers across various industries.
• 16,000 enterprise-level paying customers.
• Platform consolidates multiple monitoring tools into one solution.
• Helps detect issues before customers experience performance problems.
• Market challenge: customers using disparate observability solutions.
• Reduces TCO by eliminating multiple monitoring tools.
• Targets VPs, CTOs, CIOs, and sometimes CEOs.
• Decade-long partnership with AWS.
• Platform built on largest unified telemetry data cloud.
• Uses AWS Graviton instances and Amazon EKS.
• AWS partnership enables innovation and customer trust.
• Three AI approaches: user assistance, LLM monitoring, faster insights.
• New Relic AI helps write query language (NURCLs).
• Monitors LLMs in customer environments.
• Uses AI to accelerate incident resolution.
• Lesson learned: should have started AI implementation sooner.
• Many customers still cautiously adopting AI technologies.
• Goal: continue growth with AWS partnership.
• Offers compute-based pricing model.
• Customers only pay for what they use.
• Announced one-step AWS monitoring for enterprise scale.
• Amazon Q Business and New Relic AI integration.
• Agent-to-agent AI eliminates data silos.
• Embeds performance insights into business application workflows.

Participants:

• Arnie Lopez – SVP Chief Customer Officer, New Relic

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

PDI Technologies’ Steve Antonakakis shares how his company is implementing generative AI across their fuel and retail technology ecosystem through a practical, customer-focused approach using Amazon Bedrock.

Topics Include:

• PDI's COO/CTO discussing generative AI implementation
• Practical step-by-step approach to AI integration
• Testing in real-world settings with customer feedback
• AWS Bedrock and Nova models exceeded expectations
• Early adoption phase with huge potential
• Fuel/retail industry processes many in-person transactions
• PDI began in 1983 as ERP provider
• Grew through 33+ acquisitions
• Provides end-to-end fuel industry solutions
• Owns GasBuddy and Shell Fuel Rewards
• Processes millions of transactions daily
• Generative AI fits into their intelligence plane architecture
• AWS Bedrock integrates well with existing infrastructure
• Focus on trusted, controlled, accountable AI
• Productizing AI features harder than traditional features
• Created entrepreneurial structure alongside regular product teams
• Team designed to fail fast but stay customer-focused
• AI features can access databases without disrupting applications
• Customers want summarization across different business areas
• AI provides insights and actionable recommendations
• Conversational AI replaces traditional reporting limitations
• Working closely with customers to solve problems together
• Beyond prototyping phase, now in implementation
• AWS Nova provides excellent cost-to-value ratio
• Focus on measuring customer value over immediate profitability
• RFP use case saved half a million dollars
• Early prompts were massive, now more structured
• Setting realistic customer expectations is important
• Data security approach same as other applications
• Treating AI outputs with same data classification standards

Participants:

• Steve Antonakakis – COO & CTO, Retail & Energy, PDI Technologies

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

AWS partners Braze, Qualtrics, and Tealium share strategies for marketplace success, vertical industry expansion, and generative AI integration that have driven significant business growth.

Topics Include:

• Jason Warren introduces AWS Business Application Partnerships panel.
• Three key topics: Marketplace Strategy, Vertical Expansion, Gen-AI Integration.
• Alex Rees of Braze, Matthew Gray of Tealium, and Jason Mann of Qualtrics join discussion.
• Braze experienced triple-digit percentage growth through AWS Marketplace.
• Braze dedicating resources specifically to Marketplace procurement.
• Tealium accelerated deal velocity by listing on Marketplace.
• Tealium saw broader use case expansion with AWS co-selling.
• Qualtrics views Marketplace listing as earning a "diploma."
• Understanding AWS incentives and metrics is crucial.
• Knowing AWS "love language" helps partnership success.
• Braze saw transaction volume increase between Q1 and Q4.
• Aligning with industry verticals unlocked faster growth.
• Tealium sees bigger deals and faster close times.
• Tealium moved from transactional to strategic marketplace approach.
• Private offers work well for complex enterprise agreements.
• Qualtrics measures AWS partnership through "influence, intel, introductions."
• AWS relationships help navigate IT and procurement challenges.
• Propensity-to-buy data guides AWS engagement strategy.
• Marketplace strategy evolving with new capabilities and international expansion.
• Brazilian marketplace distribution reduces currency and tax challenges.
• Partnership evolution: sell first, then market, then co-innovate.
• Braze penetrated airline market through AWS Travel & Hospitality.
• RFP introductions show tangible partnership benefits.
• Tealium partnering with Virgin Australia and United Airlines.
• MUFG bank case study shows joint AWS-Tealium success.
• Qualtrics won awards despite not completing formal competencies.
• Focus on fewer verticals yields better results.
• Gen AI brings both opportunities and regulatory concerns.
• First-party data rights critical for AI implementation.
• AWS Bedrock integration provides security and prescriptive solutions.

Participants:

• Alex Rees – Director Tech Partnerships, Braze
• Jason Mann – Global AWS Alliance Lead, Qualtrics
• Matthew Gray - SVP, Partnerships & Alliances, Tealium
• Jason Warren - Head of Business Applications ISV Partnerships (Americas), AWS

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

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

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

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

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