AWS for Software Companies Podcast

• Ep172: Scaling AI from Day One: SS&C Blue Prism on Governance, Guardrails, and Growth

  SS&C Blue Prism's VP reveals how they achieved $200M annual savings and $600M revenue growth by deploying 3,000 AI agents, processing 6 million documents monthly as their own first customer.Topics Include:SS&C Blue Prism evolved from RPA leader to agentic automation provider over 25 yearsServes 22,000 clients in regulated industries like financial services, healthcare, manufacturing, and retailOffers AI agents, governance gateway, and secure enterprise chat leveraging AWS BedrockAs "customer zero," they deployed 3,000 agents processing 6 million documents monthlyGenerated $200M annual savings and $600M revenue growth using their own technologyFinancial services client unlocked unstructured document processing previously impossible with traditional automationHealthcare client's AI processes MRIs more accurately than human radiologistsKey lesson: Focus on business outcomes first, not just implementing AI everywhereCritical insight: Plan for scale on day one, not after pilots succeedAWS Marketplace streamlined purchasing, especially in challenging Latin American marketsFuture vision: B2A economy where agents negotiate parking, shopping, and services autonomouslyPredicts agent-to-agent communication will revolutionize healthcare monitoring and wealth managementParticipants:Satish Shenoy – Global Vice President, Technology Alliances and GenAI GTM, SS&C Blue PrismSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

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• Ep171: Responsible Business Innovation with Generative AI

  ** AWS re:Invent 2025 Dec 1-5, Las Vegas - Register Here! **Three enterprise AI leaders from Archer, Demandbase, and Highspot reveal how top companies are implementing AI responsibly while navigating data privacy, bias prevention, and regulatory compliance challenges.Topics Include:AWS Security GM Brian Shadpour hosts three AI leaders discussing responsible enterprise deploymentDemandbase's Umberto Milletti explains tenant-based models ensuring first-party customer data remains confidentialHighspot's Oliver Sharp uses behavior-specific feedback frameworks to eliminate bias in sales assessmentsReal-time AI evaluation proves challenging when assessing dynamic sales conversations and customer interactionsCompanies create "second-party data" networks where customers opt-in to share insights collectivelyOpen-source models gain traction but require significant expertise for enterprise-grade implementationEU AI Act mandates human oversight, reshaping how companies design AI systems globallyArcher's Kayvan Alikhani extends identity management principles from web applications to AI agentsUnattended AI agents performing tasks autonomously create new security and accountability challengesHuman-in-the-loop oversight remains essential, especially for high-stakes decisions affecting customersFuture challenge: Determining when AI accuracy justifies removing costly human oversightEnterprise data hygiene becomes critical as AI systems need clean, reviewed internal dataParticipants:Kayvan Alikhani - Global Head of Engineering- Emerging Solutions, Archer Integrated Risk ManagementUmberto Milletti - Chief R&D Officer, DemandbaseOliver Sharp - Co-Founder & Chief AI Officer, HighspotBrian Shadpour - General Manager, Security, Amazon Web ServicesSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

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• Ep170: From Open Source to AI Agents – Inside SnapLogic’s Transformation with AWS

  ** AWS re:Invent 2025 Dec 1-5, Las Vegas - Register Here! **SnapLogic CTO Jeremiah Stone reveals how they evolved from open-source to AI-powered integration platform, doubled AI adoption with one UX change, and delivers measurable enterprise ROI.Topics Include:SnapLogic CTO shares their decade-long journey building AI-powered integration with AWS partnership.SnapLogic drives "human cost of integration to zero" for thousands of global companies.Started as open-source project, pivoted to cloud in 2015 with AWS infrastructure.Began AI workloads in 2018, predicting next steps in integration workflows using models.Became AWS Bedrock launch partner, completely reinventing their product for generative AI era.SnapLogic lives through transformations first, then credibly helps ISV customers do same.Helped Adobe migrate entire CRM from Salesforce to Microsoft over single weekend.Built normalized data architecture using S3, Iceberg, Glue for analytics-ready enterprise data.SnapGPT copilot converts plain language prompts into complete integration pipelines in minutes.Live demo shows generating Salesforce-to-Redshift pipeline with filters using natural language commands.Small UX tweak adding helpful header doubled monthly active users of SnapGPT.Changed legal agreements in 2017 to capture metadata, enabling AI features years later.Agent Creator delivers ROI across customers: Inspirant, Core Plus, AstraZeneca use cases.SnapLogic's own finance team cut order reconciliation from 40 hours monthly to 90 minutes.Key lessons: governance first, understand business impact, use AWS native patterns consistently.Participants:Jeremiah Stone – Chief Technical Officer, SnapLogicOlawale Oladehin – Managing Director, NAMER Technology Segments, Amazon Web ServicesSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

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• Ep169: Connecting Everything Everywhere: How Boomi Powers Enterprise Integration with AWS

  ** AWS re:Invent 2025 Dec 1-5, Las Vegas - Register Here! **Vice President of Solution Engineering Chris Timmerman reveals how Boomi's integration platform evolved into a no-code AI agent builder on AWS, serving 22,000 enterprises while solving the 95% failure rate in AI production deployments.Topics Include:Chris Timmerman shares his 9-year journey from Field CTO to VP Solution Engineering at BoomiBoomi connects cloud and on-premise systems, helping enterprises move data seamlessly since early 2000sThe platform serves 22,000+ customers, from order-to-cash processes to complex M&A integrationsNew CEO Steve Lucas pivoted Boomi toward generative AI when ChatGPT emergedBoomi approaches AI three ways: internal automation, product enhancement, and customer enablementAI Agent Studio lets users build agents on AWS Bedrock without writing codeAgent Garden marketplace allows partners to share specialized agents for Salesforce, NetSuite, and moreChris reveals 95% of enterprise AI projects fail to reach production due to data issuesAWS partnership since 2018 provides infrastructure plus hands-on engineering collaboration for problem-solvingHackathons with AWS engineers generate excitement and innovative solutions for customer challengesChris advises new AWS partners: "Don't be afraid to ask for help" and be transparentFuture vision: Partner with market leaders like AWS rather than reinvent foundational AI frameworksParticipants:Christopher Timmerman – Vice President, Solution Engineering, BoomiSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

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• Ep168: Scaling Agentic Workloads: Why Reliable Infrastructure is Non-Negotiable for Enterprise AI by Anyscale

  ** AWS re:Invent 2025 Dec 1-5, Las Vegas - Register Here! **Learn how Anyscale's Ray platform enables companies like Instacart to supercharge their model training while Amazon saves heavily by shifting to Ray's multimodal capabilities.Topics Include:Ray originated at UC Berkeley when PhD students spent more time building clusters than ML modelsAnyscale now launches 1 million clusters monthly with contributions from OpenAI, Uber, Google, CoinbaseInstacart achieved 10-100x increase in model training data using Ray's scaling capabilitiesML evolved from single-node Pandas/NumPy to distributed Spark, now Ray for multimodal dataRay Core transforms simple Python functions into distributed tasks across massive compute clustersHigher-level Ray libraries simplify data processing, model training, hyperparameter tuning, and model servingAnyscale platform adds production features: auto-restart, logging, observability, and zone-aware schedulingUnlike Spark's CPU-only approach, Ray handles both CPUs and GPUs for multimodal workloadsRay enables LLM post-training and fine-tuning using reinforcement learning on enterprise dataMulti-agent systems can scale automatically with Ray Serve handling thousands of requests per secondAnyscale leverages AWS infrastructure while keeping customer data within their own VPCsRay supports EC2, EKS, and HyperPod with features like fractional GPU usage and auto-scalingParticipants:Sharath Cholleti – Member of Technical Staff, AnyscaleSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

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