AWS for Software Companies Podcast

Amazon Web Services
  • 5.0 (10)
  • 科技
  • 两周一更

Stay current on new cloud trends. Top software companies, respected industry analysts, and experienced consultants join Amazon Web Services leaders to talk about the cloud topics that matter to you—including the latest in AI, migration, Software-as-a-Service, and more. We produce new episodes regularly.

  1. Ep142: Transforming ISV Businesses Through Modern Data Platforms with Coveo, DTEX Systems and Honeycomb

    1天前

    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 software Participants: 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 Services Further Links: Coveo: Website – LinkedIn – AWS MarketplaceDTEX Systems: Website – LinkedIn – AWS MarketplaceHoneycomb.io: Website – LinkedIn – AWS Marketplace See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

    44 分钟
  2. Ep141: Securing Identities in the Age of AI Agents with Bhwana Singh, CTO of Okta

    4天前

    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 efforts Participants: Bhawna Singh – CTO, Customer Identity, Okta See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

    28 分钟
  3. Ep140: Architecting Agentic AI Systems - Technical Insights for ISVs with Anyscale, CrewAI and Encrypt AI

    6天前

    Ep140: Architecting Agentic AI Systems - Technical Insights for ISVs with Anyscale, CrewAI and Encrypt AI

    A panel discussion with AI industry leaders revealing how enterprises are scaling AI today, with predictions on coming breakthroughs for AI and the impact on Fortune 500 companies and beyond. Topics Include: Three technical leaders discuss production challenges: security, interoperability, and scaling agentic systemsPanelists represent Enkrypt (security), Anyscale (infrastructure), and CrewAI (agent orchestration platforms)Industry moving from flashy demos to dependable agents with real business outcomesBreakthrough examples include 70-page IRS form processing and multimodal workflow automationMultimodal data integration becoming crucial - incorporating video, audio, screenshots into decisionsLess than 10% of future applications expected to be text-onlyCompanies shifting from experimenting with individual models to deploying agent networksNeed for governance frameworks as enterprises scale to hundreds of agentsGrowing software stack complexity requires specialized infrastructure between applications and GPUsSecurity teams need centralized visibility across fragmented agent deployments across enterprisesExisting industry regulations apply to AI services - no special AI laws neededInteroperability standards debate: MCP gaining adoption while A2A seems premature solutionMCP shows higher API reliability than OpenAI tool calling for implementationsMultimodal systems more vulnerable to attacks but value proposition too high ignoreFortune 500 company automated price operations approval process using 630 brands data87% of enterprise customers deploy agents in private VPCs or on-premises infrastructureSpecialized AI systems needed to oversee other agents at machine speed scalesCost optimization through model specialization rather than always using most powerful modelsFuture learning may happen through context/prompting rather than traditional weight fine-tuningPredictions include AI meeting moderators and agents working autonomously for hours Participants: Robert Nishihara - Co-founder, AnyscaleJoão Moura - CEO, CrewAISahil Agarwal - Co-Founder & CEO, Enkrypt AIJillian D’Arcy - Sr. ISV Sales Leader, Amazon Web Services Further Links: Anyscale – Website  | LinkedIn  | AWS MarketplaceCrewAI - Website  | LinkedIn  | AWS MarketplaceEnkrypt AI - Website  | LinkedIn  | AWS Marketplace See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

    44 分钟
  4. Ep139: Human-in-the-Loop by Design: Building AI Systems Responsibly

    9月1日

    Ep139: Human-in-the-Loop by Design: Building AI Systems Responsibly

    AI executives from Archer, Demandbase and Highspot and AWS reveal how they're tackling AI's biggest challenges—from securing data, managing regulatory changes and keeping humans in the loop. Topics Include: Three AI leaders introduce their companies: Archer, Demandbase and Highspot's approaches to enterprise AIDemandbase's data strategy: Customer data stays isolated, shared data requires consent, public sources fuel trainingGeographic complexity: AI compliance varies dramatically between Germany, US, Canada, and California regulationsHighSpot tackles sales bias: Granular questions replace generic assessments for more accurate rep evaluationsSBI framework applied to AI: Specific behavioral observations create better, more actionable sales coachingAI transparency through citations: Timestamped evidence lets managers verify AI feedback and catch hallucinationsArcher handles 20-30K monthly regulations: AI helps enterprises manage overwhelming compliance requirements at scaleTwo compliance types explained: Operational (common across companies) versus business-specific regulatory requirementsEU AI Act adoption: US companies embracing European framework for responsible AI governanceHuman oversight becomes mandatory: Expert-in-the-loop reviews ensure AI decisions remain correctable and auditableThe bigger AI risk: Companies face greater danger from AI inaction than AI adoptionAgentic AI security challenges: Data layers must enforce permissions before AI access, not afterAI agents need identity management: Same access controls apply whether human clicks or AI actsHuman oversight in high stakes: Chief compliance officers demand transparency and correction capabilitiesFuture challenge identified: 80% of enterprise data behind firewalls remains invisible to AI models Participants: 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 Services Further Links: Archer Integrated Risk Management: Website – LinkedIn – AWS MarketplaceDemandbase: Website – LinkedIn – AWS MarketplaceHighspot: Website – LinkedIn – AWS Marketplace See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

    40 分钟
  5. Ep138: The Future of Agentic AI – Challenges and Opportunities with Rob McGrorty

    8月29日

    Ep138: The Future of Agentic AI – Challenges and Opportunities with Rob McGrorty

    In a fascinating discussion, Rob McGrorty, Product Leader of Agents at Amazon AGI Lab, reveals how rapidly AI agents are evolving with corporate adoption exploding as companies race to deploy production agents and the challenges and advantages they’re experiencing. Topics Include: GenAI adoption outpaces all previous tech waves, growing faster than computers or internetEarly adopters tackle complex tasks while newcomers still use basic text manipulation featuresAI models double their single-call task capabilities every seven months, exponentially increasing powerAccelerating progress makes yesterday's magic mundane, unlocking mass creativity and customer demandAgents represent natural evolution: chatbots answered questions, now agents autonomously accomplish tasksAmazon's browser agent finds apartments, maps distances, ranks options using multiple transit modesCorporate adoption exploded: 33% piloting agents in 2024, 67% moving to production nowTwo main agent types today: API calling with tool use, browser automationCurrent applications mirror "RPA 2.0" - form filling, data extraction, website QA testingFuture brings multi-agent systems, self-directing loops, and agent-to-agent negotiation scenariosMajor challenges: data privacy, oversight protocols, error responsibility, and ecosystem sustainabilityTechnical hurdles include real-time accuracy measurement, latency issues, and quality assurance frameworks Participants: Rob McGrorty – Product Leader, Agents at Amazon AGI Lab See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

    31 分钟
  6. Ep137: AI Without Borders - Extending analyst capabilities across the modern SOC

    8月27日

    Ep137: AI Without Borders - Extending analyst capabilities across the modern SOC

    Gagan Singh of Elastic discuses how agentic AI systems reduce analyst burnout by automatically triaging security alerts, resulting in measurable ROI for organizations Topics Include: AI breaks security silos between teams, data, and tools in SOCsAttackers gain system access; SOC teams have only 40 minutes to detect/containAlert overload causes analyst burnout; thousands of low-value alerts overwhelm teams dailyAI inevitable for SOCs to process data, separate false positives from real threatsAgentic systems understand environment, reason through problems, take action without hand-holdingAttack discovery capability reduces hundreds of alerts to 3-4 prioritized threat discoveriesAI provides ROI metrics: processed alerts, filtered noise, hours saved for organizationsRAG (Retrieval Augmented Generation) prevents hallucination by adding enterprise context to LLMsAWS integration uses SageMaker, Bedrock, Anthropic models with Elasticsearch vector database capabilitiesEnd-to-end LLM observability tracks costs, tokens, invocations, errors, and performance bottlenecksJunior analysts detect nation-state attacks; teams shift from reactive to proactive securityFuture requires balancing costs, data richness, sovereignty, model choice, human-machine collaboration Participants: Gagan Singh – Vice President Product Marketing, Elastic Additional Links: Elastic – LinkedIn - Website – AWS Marketplace See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

    31 分钟
  7. Ep136: Rapid7's Journey to an AI First Platform with AWS

    8月25日

    Ep136: Rapid7's Journey to an AI First Platform with AWS

    Pete Rubio reveals how Rapid7 transformed to an AI-first platform that automates security investigations and accelerates results from hours to seconds. Topics Include: Pete Rubio introduces Rapid7's journey to becoming an AI-first cybersecurity platformCybersecurity teams overwhelmed by growing attack surfaces and constant alert fatigueCustomers needed faster response times, not just more alerts coming fasterLegacy tools created silos requiring manual triage that doesn't scale effectivelyAI must turn raw security data into real-time decisions humans can trustUnified data platform correlates infrastructure, applications, identity, and business context togetherAgentic AI automates investigative work, reducing analyst tasks from hours to secondsRapid7 evaluated multiple vendors, choosing AWS for performance, cost, and flexibilityNova models delivered unmatched performance for global scaling at controlled costsBedrock provided secure model deployment with governance and data privacy boundariesAWS partnership enabled co-development and rapid iteration beyond typical vendor relationshipsTransparent AI shows customers how models reach conclusions before automated actionsSOC analyst expertise continuously trains models with real-time security intelligenceGovernance frameworks and guardrails implemented from day one, not retrofitted laterFuture plans include customer AI integration and bring-your-own-model capabilities Participants: Pete Rubio – Senior Vice President, Platform & Engineering, Rapid7 Additional Links: Rapid 7 – LinkedIn - Website – AWS Marketplace See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

    25 分钟
  8. Ep135: Petabytes and Milliseconds: How Panther scales Security Monitoring with Cloud-Native AI

    8月22日

    Ep135: Petabytes and Milliseconds: How Panther scales Security Monitoring with Cloud-Native AI

    Panther CEO William Lowe explains how integrating Amazon Bedrock AI into their security platform delivered 50% faster alert resolution for enterprise customers while maintaining the trust and control that security practitioners demand. Topics Include: Panther CEO explains how Amazon partnership accelerates security outcomes for customersCloud-native security platform delivers 100% visibility across enterprise environments at scaleCustomers like Dropbox and Coinbase successfully replaced Splunk with Panther's solutionPlatform processes petabytes monthly with impressive 2.3-minute average threat detection timeCritical gap identified: alert resolution still takes 8 hours despite fast detectionSecurity teams overwhelmed by growing attack surfaces and severe talent burnoutConstant context switching across tools creates inefficiency and organizational collaboration problemsAI integration with Amazon Bedrock designed to accelerate security team decision-makingFour trust principles: verifiable actions, secure design, human control, customer data ownershipResults show 50% faster alert triage; future includes Slack integration and automation Participants: ·        William H Lowe – CEO, Panther See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

    11 分钟
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Stay current on new cloud trends. Top software companies, respected industry analysts, and experienced consultants join Amazon Web Services leaders to talk about the cloud topics that matter to you—including the latest in AI, migration, Software-as-a-Service, and more. We produce new episodes regularly.

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