Curious how AI can query your enterprise data without moving it or making things up? AWS and Teradata break down a trustworthy analyst agent built for real production use.

Topics Include:

• Neha Wadhera (AWS) introduces Trinath Yarlagadda and the Teradata Analyst Agent
• Enterprise AI data prep is costly, stalling most orgs at experimentation
• Agent answers plain-English questions via traceable SQL, zero data movement
• Barrier removal drives 3.7x ROI and 40% productivity gains
• Healthcare demo setup: hospital COPD readmissions, ~$10K cost per incident
• Four design principles: traceability, no data movement, deterministic-first, governance as code
• Main orchestrator agent plans, writes SQL, calls Teradata MCP server
• Complex questions escalate to a context-isolated data scientist agent
• Built on Claude Agent SDK, running Bedrock Claude Sonnet/Haiku/Opus
• Live demo: COPD readmission rates explored through iterative agent reasoning
• Delegation demo: data scientist agent runs in-database analysis, surfaces factors
• Pre/post tool hooks log every step and cost to CloudWatch
• Agent hosted on Amazon Bedrock AgentCore, fully serverless and scalable
• AgentCore delivers runtime, memory, identity, and observability out of the box
• Lessons learned: guardrails first, deterministic ops, multi-agent registry, ongoing evaluation

Participants:

• Trinath Yarlagadda – Principal Solution Architect – Agentic AI, Teradata
• Neha Wadhera – Sr 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/

Learn how Vercel's "self-driving infrastructure" vision pairs with AWS databases to eliminate backend friction, securely cutting Aurora Serverless creation time from minutes to seconds.

Topics Include:

• Hedieh Zandi (Vercel) and Manbeen Kohli (AWS) introduce prompt-to-production session
• Vercel powers 18 million developers, maintains Next.js and AI SDK
• Vercel's agentic infrastructure runs on AWS Lambda, CloudFront, and S3
• AI now generates frontend, APIs, and workflows for small teams
• Backend friction remains: credentials, provisioning, database configuration still hard
• Vercel envisions "self-driving infrastructure" that adapts automatically to apps
• New AWS partnership brings native Aurora DSQL and Postgres integration
• Manbeen explains databases now built into Vercel Marketplace and v0
• Aurora Serverless database creation sped up from minutes to seconds
• Aurora Postgres, DynamoDB, and DSQL scale prototypes without rewrites
• Pre-configured templates help builders start RAG or shopping AI apps
• Database security uses OIDC and IAM tokens, no stored passwords
• AWS chosen for agents: low latency, autonomy, one-click simplicity
• skills.sh gives agents reusable instructions, mirrors AWS Kiro's "powers"
• v0 lets users build full-stack apps using natural language prompts
• v0 uses Bedrock models and deploys directly on Vercel infrastructure
• Live demo: v0 builds restaurant app, provisions database, adds Stripe checkout
• Demo ends at AWS console; Rauch quote and hackathon close session

Participants:

• Hedieh Zandi - Product Lead, Vercel
• Manbeen Kohli - Director of Product Management, Aurora and RDS Databases, 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/

Kaltura's Ruthie Eisenberg and Yair Neumann reveal how the video giant is reinventing itself as an agentic digital experience company built on AI avatars and hyper-personalized content.

Topics Include:

• Kaltura founded 2006, went public on NASDAQ in 2021.
• Kaltura reinventing itself from video company to agentic digital experience company.
• Shift from static content delivery to hyper-personalized conversational experiences.
• Partners and customers now demand intelligence, not just video infrastructure.
• Kaltura's mission: powering agentic experiences across customer and learner journeys.
• AWS co-sell motion strengthened as Kaltura runs on AWS AI infrastructure.
• Camille used a Kaltura avatar to scale her own presentations.
• Most enterprise websites bury content behind thousands of static links.
• Kaltura builds personalised web pages on the fly, in real time.
• Over 80% of content users see is surfaced for the very first time.
• Acquisitions of eSelf.ai and PassFactory complete Kaltura's agentic content flywheel.
• PassFactory answers: what should this specific person see next?
• eSelf.ai enables multimodal conversational avatars that guide users emotionally.
• 20 years of behavioral data underpins Kaltura's content intelligence advantage.
• GPU scarcity and compute costs shape every AI architecture decision Kaltura makes.
• Kaltura optimises model tiers — strongest for planning, lighter models for execution.
• Fidelity, speed, and cost form a constant triangle in every AI product decision.
• Go-to-market and product teams now work closer together than ever before.
• Pricing shifting from seat-based SaaS to consumption and outcome-based models.
• Kaltura co-creating pricing frameworks with customers across different verticals.
• Internal product agent now handles research, stories, and data analysis autonomously.
• Small two-to-three person squads move fastest in the current AI environment.
• Yair's advice: fail at least once a week, succeed once a quarter.
• Kaltura scaled its CEO via avatar for a live investor earnings call.
• Ruthie's advice: keep the customer at the centre of every single decision.

Participants:

• Ruthie Eisenberg – Vice President, Strategic Partnerships, Kaltura
• Yair Neumann – Senior Vice President of Product, Kaltura
• Kamil Davidov – Sales Leader Israel ISV-BizApps, Amazon Web Services
• Johan Broman – EMEA ISV Head of Solutions Architecture, 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/

With 250,000 customers and $1.2B in revenue, Monday.com's CPTO explains why they threw out their roadmap and rebuilt everything around agentic AI.

Topics Include:

• Daniel Lereya joined Monday.com when it had just 30 people and five engineers.
• He grew the R&D org from five engineers to roughly 900 over a decade.
• Three years ago Daniel became Monday.com's first ever CPTO.
• Monday.com initially approached AI by adding small features across the product.
• They called this early phase "sprinkling AI dust" — helpful but not transformative.
• A pivotal board meeting made Daniel realise AI hadn't changed Monday's core value.
• Monday.com decided to rethink its mission from first principles around AI.
• The new mission: AI agents that actually execute work, not just manage it.
• AI gives businesses an "infinite workforce" regardless of company size.
• Agents can now do hyper-personalised work at a scale humans simply cannot.
• Monday's platform puts agents at the centre, replacing boards and dashboards.
• Shared context and human-in-the-loop handoffs make their agents uniquely powerful.
• Monday ran an "AI month" — pausing the entire 900-person builder org to transform.
• The month rebuilt team mindset and energy, reminding staff of early startup days.
• Monday also ran an "agentic week" where every department built their own agents.
• Finance built agents to automatically match incoming payments to customer accounts.
• Scaling AI adoption internally remains the biggest challenge across businesses today.
• Monday introduced "effective AI" — balancing capability with cost efficiency.
• They acquired voice AI startup One AI to add specialised model capabilities.
• On pricing, Monday shifted to a hybrid seats-plus-AI-credits consumption model.

Participants:

• Daniel Lereya – Chief Product and Technology Officer, Monday.com
• Kamil Davidov – Sales Leader Israel ISV-BizApps, Amazon Web Services
• Johan Broman – EMEA ISV Head of Solutions Architecture, 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/

PagerDuty SVP Rukmini Reddy explains why AI is making software operations exponentially more complex — and why the companies that learn and recover fastest will be the ones that win.

Topics Include:

• PagerDuty powers critical digital operations for enterprises and AI-native companies.
• Founded by early AWS employees who experienced always-on system failures firsthand.
• The platform evolved from simple alerting into a full operational intelligence platform.
• Complexity exploded with microservices, cloud-native infrastructure, and multi-cloud environments.
• Reliability must be a core value — not an operational afterthought.
• PagerDuty's culture champions the customer above everything else.
• Employee recognition extends beyond sales to celebrate the whole business.
• AI is accelerating software creation but making operations far more complex.
• AI fails differently — silently, unpredictably, with a much larger blast radius.
• Enterprises should leverage their operational history as a competitive AI asset.
• AI-native companies must build operational resilience early, not bolt it on later.
• The winners won't build fastest — they'll learn and recover fastest.

Participants:

• Rukmini Reddy – Senior Vice President of Engineering, PagerDuty

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

From cracked data foundations to multi-agent AI, Starburst Data's co-founder shares hard-won lessons on getting the right data, not just more of it.

Topics Include:

• Matthew Fuller, co-founder and VP of Product at Starburst Data, joins the show.
• Starburst is built on Trino, a fast SQL engine for federated data queries.
• Their platform lets users query data across lakes, stores, and databases seamlessly.
• Governed "data products" give organizations access to their full data estate in context.
• A strong data foundation is essential before any AI use case can succeed.
• AI doesn't create data problems — it exposes the cracks already there.
• Common mistake: assuming everyone in an org defines "customer" or "revenue" the same way.
• More data isn't always better — getting the right data is what matters.
• Customers include HSBC, Comcast, Zalando, ZoomInfo, and DBS, many running on AWS.
• AWS partnership spans technical support, SLA reliability, and proactive product briefings.
• Advice for product leaders: always anchor new technology back to the customer problem.
• 2026 will be defined by specialized multi-agents working together autonomously.

Participants:

• Matt Fuller – Co-Founder, Vice President of Product, Starburst Data

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

Find out why the world's largest banks and enterprises trust CockroachDB for mission-critical infrastructure, and what a decade of AWS partnership means for the future of cloud-native data.

Topics Include:

• Cockroach Labs makes CockroachDB, a distributed SQL database built for resilience.
• It delivers cloud-native consistency that legacy relational databases simply cannot match.
• The name "cockroach" reflects survivability — it's designed to never go down.
• Target customers include major banks, trading platforms, retailers, and gaming companies.
• AI is forcing enterprises to accelerate database modernization from the board level down.
• AWS has been a foundational cloud partner for Cockroach Labs for a decade.
• The CockroachDB-AWS integration spans EC2, S3, Bedrock, and Amazon Q-Transform.
• AWS partnership shapes both product roadmap decisions and go-to-market execution.
• New partners should educate themselves first — AWS programs are deep and extensive.
• CockroachDB now supports native vector search for RAG and generative AI applications.
• Agentic AI could mean trillions of digital agents demanding real-time data infrastructure.
• Database modernization and AI adoption will only accelerate dramatically through 2027.

Participants:

• Cassie Zimmerman – Senior Director, Global Strategic Partnerships, Cockroach Labs

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

Greg Murphy of Vectra AI explains why no single security tool is enough in 2026, and how AI is transforming overwhelmed security teams into lean, highly responsive defense operations.

Topics Include:

• Vectra AI helps enterprises detect and respond to cyberattacks before they become breaches.
• CISOs face millions of alerts monthly with dangerously understaffed security teams.
• Vectra pioneered AI-driven triage to prioritize only the most critical threats.
• The result: analysts act on two or three alerts, not thousands.
• Generative AI is now actively being weaponized by sophisticated bad actors.
• The first fully AI-orchestrated cyberattack by a nation state has already happened.
• Vectra and AWS Bedrock are building autonomous agents to fight back.
• Agentic AI can investigate thousands of incidents and surface only what matters.
• Over-reliance on single tools like EDR leaves dangerous gaps in defense.
• Modern attacks move fluidly across identity, network, and cloud environments simultaneously.
• AI stitches cross-surface signals together, revealing attacks hidden in isolated events.
• Best practice: assume breach, expand your network definition, and layer best-of-breed solutions.

Participants:

• Greg Murphy – Chief Business Officer, Vectra AI

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

If you're betting on agentic AI, hear directly from the builders navigating the challenges, innovating pricing models, and creating the coming reality where every employee manages thousands of agents.

Topics Include:

• Four panelists represent the full AI stack: build, run, secure, monitor.
• Agentic AI moved faster than anyone predicted just 18 months ago.
• Writer AI's no-code agent builder missed both its target personas entirely.
• Non-technical users now just prompt agents instead of building workflows.
• Fireworks AI processes over ten trillion tokens daily across open models.
• DeepSeek's Christmas release tripled Fireworks' capacity needs almost overnight.
• Okta identified agent identity as a security problem from day one.
• 91% of organizations are already using AI agents in some capacity.
• Datadog evolved naturally from dashboards to autonomous investigative agents.
• Bits.ai agents now diagnose production incidents before engineers wake up.
• Trust requires explainability — black-box agents stall enterprise adoption cold.
• Human-in-the-loop remains essential; risk tolerance varies wildly by organization.
• Writer AI compressed a four-month retail workflow down to one week.
• Multi-provider inference consistency is one of the hardest unsolved infrastructure problems.
• Agentic pricing models are fundamentally broken for enterprise budget planning today.
• Agents managing agents means every employee becomes a manager of thousands.
• POC data gaps are the most underrated blocker to production deployment.
• Security must be designed in from the start — retrofitting is painful.
• Build evaluations first so you know if you're actually improving anything.
• Find your uniquely differentiated data and build your agentic bet there.

Participants:

• Yannick Guillerm – Regional Manager, Sales Engineering, Datadog
• Ray Thai – Director of Product Management, Fireworks AI
• Andrew Yu – Vice President of Engineering, Okta
• Matan-Paul Shetrit – Director of Product Management, Writer AI
• Moderator: Carol Potts – General Manager, North America ISV Sales, AWS

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

Asana CPO Arnab Bose breaks down how AI agents are transforming collaborative work management with multiplayer AI teammates that any team member can coach and correct.

Topics Include:

• Asana is a collaborative work management platform used by 170,000+ companies worldwide.
• The "Pyramid of Clarity" connects individual tasks all the way up to company strategy.
• Asana's "work graph" maps tasks, teams, projects, and portfolios in one connected system.
• Generative AI now converts unstructured data like emails into structured project plans.
• Asana integrates directly with AWS, Gemini, and Claude to automate that conversion.
• AI Teammates are first-party agents that take on and complete tasks inside Asana.
• These agents work in multiplayer mode — visible, collaborative, and team-correctable.
• A third AI unlock is coming: letting any external agent builder plug into Asana's interface.
• Asana runs entirely on AWS, including a new FedRAMP moderate GovCloud deployment.
• AWS Marketplace listings help customers transact faster using existing AWS credits.
• Arnab advises startups to bet on AWS long-term rather than chasing short-term LLM trends.
• His 2026 prediction: multi-agent orchestration standards will be the enterprise AI battleground.

Participants:

• Arnab Bose – Chief Product Officer, Asana

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