AWS for Software Companies Podcast

• Ep145: Transforming the CFO's Office with Amazon Bedrock

  Learn how Amazon Bedrock enabled Prophix to build enterprise-grade AI agents that transform secure CFO workflows, while delivering real-time financial intelligence through advanced agentic architecture. Topics Include:AWS and Prophix leaders discuss building autonomous AI agents for financial managementAI agents defined: autonomous systems that reason, plan, and execute tasks independentlyEvolution from simple chatbots to collaborative multi-agent systems solving complex problemsCore agent components: cognitive planning module, memory systems, and external tool integrationsProphix: 30-year financial software company serving 3,500 CFO offices globally across industriesProphix One Intelligence: platform-level AI service powering predictions, analysis, and automationCustomer concerns addressed: data privacy, role-based security, accuracy, and cost controlRejected "models in the sky" approach for AWS Bedrock's managed, controllable infrastructureAgentic architecture: LLMs generate API parameters instead of processing massive datasetsReal-time data access, automatic security inheritance, and A/B testing capabilities achievedLive demo: automated budgeting workflows, natural language queries, and autonomous task executionAWS introduces AgentCore platform to simplify agent development for enterprise customersParticipants:Anurag Yagnik – Chief Technology Officer, ProphixDeborshi Choudhury – Sr Solutions Architect – ISV, Amazon Web ServicesFurther Links:Prophix: Website | LinkedIn See 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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• Ep144: 8 Trillion Observations a Week: How Arctic Wolf Uses AI to Stop Ransomware Attacks

  Dean Teffer of Arctic Wolf reveals how they process 8 trillion weekly security observations to find "a needle in a stack of needles," and breaks down real-world GenAI lessons learned.Topics Include:Dean Teffer, VP of AI at Arctic Wolf, discusses company's GenAI journeyArctic Wolf: decade-old security operations company serving mid-market customers globallyOperates massive security operation center, now launching AI-powered productsAI agent recently identified Black Basta ransomware attack, enabling rapid containmentDean's 15+ years in cybersecurity: traditional ML focused on detectionGenAI breakthrough allows natural language interaction with security modelsArctic Wolf processes 8 trillion weekly observations, correlating suspicious activitiesChallenge: finding specific threats in "stack of needles," not haystackSuccess measured by making human analysts faster, more consistent, scalableEvolved from treating GenAI like traditional ML to integrated workflowsKey misconception: GenAI isn't magic, needs proper data and reasoningAdvice: start with existing challenges, build flexible systems for adaptationGenAI excels at summarizing information and supporting complex decisionsFuture vision: AI handles routine threats, humans focus on creativityDemocratizing machine learning capabilities to broader range of subject expertsParticipants:Dean Teffer – Vice President of AI, Arctic WolfFurther Links:Arctic Wolf: Website | LinkedIn | AWS MarketplaceSee 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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• Ep143: Beyond Passwords: CyberArk's Vision for Human, Machine, and AI Identity Security

  CyberArk's technology leader discusses their strategy for securing against AI threats, protecting agentic AI systems, and their vision for the future in an increasingly AI-driven cybersecurity landscape.Topics Include:CyberArk celebrates recent exciting news while discussing their incredible cybersecurity journeyFounded in 1999, CyberArk pioneered privilege access management and expanded into comprehensive identity securityCompany executed textbook SaaS transformation from perpetual licensing to subscription-based cloud modelLeadership set clear customer expectations, framing SaaS shift as faster innovation deliveryAddressed customer concerns about cost predictability, security compliance, and data residency requirementsTechnical team implemented lift-and-shift architecture with AWS RDS and multi-tenant improvementsCorporate initiative tracked weekly metrics and milestones throughout full development lifecycle processCustomer Success evolved from transactional support to strategic partnership embedded in security journeysAWS partnership fundamental to cloud journey with 25+ integrations and Marketplace collaborationAI strategy focuses on three pillars: using AI, securing against AI threatsFuture 12-24 months: continue securing all identities while expanding AI capabilities and solutionsAWS partnership expanding in 2025 leveraging machine identity leadership and GenAI advancesParticipants:Peretz Regev – Chief Product & Technology Officer, CyberArkBoaz Ziniman – Principal Developer Advocate - EMEA, Amazon Web ServicesFurther Links:· CyberArk: Website – LinkedIn – AWS MarketplaceSee 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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• Ep142: Transforming ISV Businesses Through Modern Data Platforms with Coveo, DTEX Systems and Honeycomb

  Three leading ISV executives from Coveo, DTEX Systems and Honeycomb, reveal how companies with proprietary datasets are gaining unbeatable competitive advantages in the AI era and share real-world strategies how you have similar outcomes.Topics Include:Panel introduces three ISV leaders discussing data platform transformation for AIDTEX focuses on insider threats, Coveo on enterprise search, Honeycomb on observabilityCompanies with proprietary datasets gain strongest competitive advantage in AI transformationData gravity concept: LLMs learning from unique datasets create defensible business positionsCoveo maintains unified enterprise index with real-time content and access rights syncHoneycomb enables subsecond queries for analyzing logs, traces, and metrics at scaleMulti-tenant architectures balance shared infrastructure benefits with single-tenant data separationCoveo deployed 140,000 times last year using mostly multi-tenant, some single-tenant componentsDTEX scaled from thousands to hundreds of thousands endpoints after architectural transformationCapital One partnership taught DTEX how to break monolithic architecture into servicesApache Iceberg and open table formats enable interoperability without data duplicationHoneycomb built custom format following similar patterns with hot/cold storage tiersBusiness data catalogs become critical for AI agents understanding dataset contextMCP servers allow AI systems to leverage structured cybersecurity datasets effectivelyDTEX used Cursor with their data to identify North Korean threat actorsReal-time AI data needs balanced with costs using right models for jobsCaching strategies and precise context reduce expensive LLM inference calls unnecessarilySearch remains essential for enterprise AI to prevent hallucination and access informationROI measurement focuses on cost reduction, analyst efficiency, and measurable business outcomesKey takeaway: invest in data structure early, context is king, AI is just softwareParticipants:Sebastien Paquet - Vice President of AI Strategy, CoveoRajan Koo - CTO, DTEX SystemsPatrick King - Head of Data, Honeycomb.ioKP Bhat - Sr Solutions Architecture Leader- Analytics & AI, Amazon Web ServicesFurther Links:Coveo: Website – LinkedIn – AWS MarketplaceDTEX Systems: Website – LinkedIn – AWS MarketplaceHoneycomb.io: Website – LinkedIn – AWS MarketplaceSee 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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• Ep141: Securing Identities in the Age of AI Agents with Bhwana Singh, CTO of Okta

  Okta's CTO Bhawna Singh discusses AI adoption, innovation and the four critical identity patterns needed to build the trust that accelerates AI implementation.Topics Include:AI innovation races ahead while adoption lags due to trust and security concernsResearch shows 82% plan AI deployment but 61% of customers demand trust firstAI coding tools dramatically reduce development time, accelerating software delivery cyclesAI interaction evolved from ChatGPT conversations to autonomous headless agents working independentlyFuture envisions millions of agents making decisions and communicating without human oversightComplex data relationships emerge as agents access multiple dynamic sources simultaneouslyTrust fundamentally starts with identity - the foundation for all AI securityFour critical identity patterns needed: authentication, API security, user confirmation, and authorizationAuthentication ensures legitimate agents while token vaults enable secure agent-to-agent communicationAsynchronous user approval prevents rogue decisions like the recent database deletion incidentIndustry standards like MCP protocol establish minimum security guardrails for interoperabilityTrust accelerates AI adoption through security, accountability, and collaborative standard-building effortsParticipants:Bhawna Singh – CTO, Customer Identity, OktaSee 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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