AWS for Software Companies Podcast

Industry leaders from Celonis and AWS explain why 2025 marks the inflection point for agentic AI and how early adopters are gaining significant competitive advantages in efficiency and innovation.Topics Include:AWS's Cristen Hughes and Celonis's Jeff Naughton discuss AI agent transformationAndy Jassy declares AI agents will fundamentally change how we workThree key trends make AI agents practical: smarter models, longer tasks, cheaper costsAI now beats humans on complex benchmarks for the first time everClaude 3.7 cracked graduate-level reasoning where humans previously dominated completelyAI evolved from brief interactions to managing sustained multi-step complex workflowsProcessing costs plummeted 99.7% making enterprise-grade AI economically viable at scaleWe're transitioning from 2023's adaptation era to 2025's human-AI collaboration eraBy 2028, AI will suggest actions to humans rather than vice versaAgents are autonomous software that plan, act, and reason independently with minimal interventionAgent workflow: receive human request, create plan, execute actions, review, adjust, deliverFour agent components: brain (LLM), memory (context), actions (tools), persona (role definition)AWS offers three building approaches: ready-made solutions, managed platform, DIY developmentKey enterprise applications: software development acceleration, customer care automation, knowledge work optimizationManual processes like accounts payable offer huge transformation opportunities through intelligent automationDeep process analysis is critical before deploying agents for maximum effectivenessCelonis pioneered process mining to help enterprises understand their actual workflow realitiesCompanies are collections of interacting processes that agents need proper context to navigateProcess intelligence provides agents with placement guidance, data feeds, monitoring, and workflow directionCelonis-AWS partnership demonstrates order management agents that automatically handle at-risk situationsParticipants:Jeff Naughton – SVP and Fellow, CelonisCristen Hughes – Solutions Architecture Leader, ISV, North America, Amazon Web ServicesFurther Links:Celonis WebsiteCelonis on AWS MarketplaceSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Justin DiPietro, Co-Founder & Chief Strategy Officer of Glia, shares how they are leveraging AI to enhance the customer experience in the highly regulated world of financial institutions.Topics Include:Glia provides voice, digital, and AI services for customer-facing and internal operationsBuilt on "channel-less architecture" unlike traditional contact centers that added channels sequentiallyOne interaction can move seamlessly between channels (voice, chat, SMS, social)AI applies across all channels simultaneously rather than per individual channel700 customers, primarily banks and credit unions, 370 employees, headquartered in New YorkTargets 3,500 banks and credit unions across the United States marketFocuses exclusively on financial services and other regulated industriesAI for regulated industries requires different approach than non-regulated businessesTraditional contact centers had trade-off between cost and quality of serviceAI enables higher quality while simultaneously decreasing costs for contact centersNumber one reason people call banks: "What's my balance?" (20% of calls)Financial services require 100% accuracy, not 99.999% due to trust requirementsUses AWS exclusively for security, reliability, and future-oriented technology accessReal-time system requires triple-hot redundancy; seconds matter for live callsWorks with Bedrock team; customers certify Bedrock rather than individual featuresShowed examples of competitors' AI giving illegal million-dollar loans at 0%"Responsible AI" separates probabilistic understanding from deterministic responses to customersUses three model types: client models, network models, and protective modelsTraditional NLP had 50% accuracy; their LLM approach achieves 100% understandingPolicy is "use Nova unless" they can't, primarily for speed benefitsParticipants:Justin DiPietro – Co-Founder & Chief Strategy Officer, GliaFurther Links:Glia WebsiteGlia AWS MarketplaceSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Ed Bailey, Field CISO at Cribl, shares how Cribl and AWS are helping customers rethink their data strategy by making it easier to modernize, reduce complexity, and unlock long-term flexibility.Topics Include:Ed Bailey introduces topic: bridging gap between security data requirements and budgetCompanies face mismatch: 10TB data needs vs 5TB licensing budget constraintsData volumes growing exponentially while budgets remain relatively flat year-over-yearIT security data differs from BI: enormous volume, variety, complexityMany companies discover 600+ data sources during SIEM migration projects50% of SIEM data remains un-accessed within 90 days of ingestionComplex data collection architectures break frequently and require excessive maintenanceTeams spend 80% time collecting data, only 20% analyzing for valueData collection and storage are costs; analytics and insights provide business valuePoor data quality creates operational chaos requiring dozens of browser tabsSOC analysts struggle with context switching across multiple disconnected systemsTraditional vendor approach: "give us all data, we'll solve problems" is outdatedData modernization requires sharing information widely across organizational business unitsData maturity model progression: patchwork → efficiency → optimization → innovationData tiering strategy: route expensive SIEM data vs cheaper data lake storageSIEM costs ~$1/GB while data lakes cost ~$0.15-0.20/GB for storageCompliance retention data should go to object storage at penny fractionsDecouple data retention from vendor tools to enable migration flexibilityCribl platform offers integrated solutions: Stream, Search, Lake, Edge componentsCustomer success: Siemens reduced 5TB to 500GB while maintaining security effectivenessParticipants:Edward Bailey – Field CISO, CriblFurther Links:Cribl WebsiteCribl on AWS MarketplaceSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Sam Johnson, Chief Customer Officer of Jamf, discusses the implementation of AI built on Amazon Bedrock that is a gamechanger in helping Jamf’s 76,000+ customers scale their device management operations.Topics Include:Sam Johnson introduces himself as Chief Customer Officer from Jamf companyJamf's 23-year mission: help organizations succeed with Apple device managementCompany manages 33+ million devices for 76,000+ customers worldwide from MinneapolisJamf has used AI since 2018 for security threat detectionReleased first customer-facing generative AI Assistant just last year in 2024Presentation covers why, how they built it, use cases, and future plansJamf serves horizontal market from small business to Fortune 500 companiesChallenge: balance powerful platform capabilities with ease of use and adoptionAI could help get best of both worlds - power and simplicityAI also increases security posture and scales user capabilities significantlyCustomers already using ChatGPT/Claude but wanted AI embedded in productBuilt into product to reduce "doorway effect" of switching digital environmentsCreated small cross-functional team to survey land and build initial trailRest of engineering organization came behind to build the production highwayTeam needed governance layer with input from security, legal, other departmentsEvaluated multiple providers but ultimately chose Amazon Bedrock for three reasonsAWS team support, large community, and integration with existing infrastructureUses Lambda, DynamoDB, CloudWatch to support the Bedrock AI implementationAI development required longer training/validation phase than typical product featuresReleased "AI Assistant" with three skills: Reference, Explain, and Search capabilitiesParticipants:Sam Johnson – Chief Customer Officer, JamfFurther Links:Jamf.comJamf on AWS MarketplaceSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Mark Stevens, SVP, Channels and Alliances, discusses how SecurityScorecard's strategic partnership with AWS enables them to scale their security solutions through cloud infrastructure, marketplace integration, and co-sell programsTopics Include:SecurityScorecard founded 10 years ago to understand third-party vendor security postureCompany has grown to 3,000 enterprise customers and 200+ partners globallyEvolved from ratings to "supply chain detection and response" over last yearSupply chain threats have doubled, creating extended attack surfaces for companiesMany organizations don't know their vendor count or vulnerabilities within supply chainsSecurityScorecard provides visibility into attack surfaces and management tools for controlGenerative AI is central to their ecosystem, leveraging AWS Bedrock extensivelyThey scan the entire internet every two days at massive scaleHave scored 12 million companies with security scorecards to dateAll workloads run on AWS cloud infrastructure as their primary platformAWS partnership provides necessary scale for managing hundreds of thousands of vendorsCase study: Identified vendor misconfigurations that could shut down 1,000 locationsOwn massive 10-year data lake with tens of millions of companiesNew managed service combines AI automation with human analysts for supportLarge organizations cannot fully automate supply chain security management yetQuality threat intelligence data now valuable to SOC teams, not just riskThird-party risk management and SOC teams are slowly converging for better securityAWS marketplace integration provides frictionless customer experience and larger dealsCo-sell programs with AWS enterprise sales teams create effective flywheel motionFuture expansion includes identity management, response actions, and internal signal managementParticipants:Mark Stevens – SVP, Channels and Alliances, SecurityScorecardFurther Links:SecurityScorecard.ioSecurityScorecard AWS MarketplaceSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Chief Product Development Officer Mitchell Johnson discusses how Sonatype protects enterprise developers from malicious open source components while keeping them productive through AI.Topics Include:Sonatype provides software supply chain solutions for enterprises using open source componentsThey serve large enterprises, government agencies, and critical infrastructure providers globallyMain challenge: keeping developers productive while maintaining secure software supply chainsCybercrime and supply chain attacks are massive, growing industries threatening developersAI adoption is happening faster than expected, profoundly changing development workflowsBad actors evolved from waiting for vulnerabilities to creating malicious componentsMalicious open source components specifically target developer and DevOps toolchainsSonatype's security research team uses AI/ML to analyze every open source componentThey can predict and block malicious components before entering customer environmentsAWS partnership helps Sonatype meet customers where they want to do businessPartnership focuses on go-to-market alignment, not just technical integrationAWS sales teams should be treated as extensions of your own sales organizationUnderstanding AWS sales structure and incentives is crucial for successful partnershipsAI development is following same pattern as open source adoption twenty years ago"Shadow AI" parallels the earlier "shadow IT" trend with open source softwareAI speeds up code generation but security review processes haven't kept paceDevelopers need a "Hippocratic Oath" - taking responsibility for AI-generated code outputWithin 24 months, professionals not skilled in AI will struggle to stay relevantSonatype's culture encourages curiosity, experimentation, and accepts failure as part of innovationTheir core mission: help developers focus on innovation, not security choresParticipants:Mitchell Johnson – Chief Product Development Officer, SonatypeFurther Links:Sonatype WebsiteSonatype on AWS MarketplaceSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Founder and CTO Alex Rice discusses how HackerOne uses generative AI to automate security workflows and prioritizing accuracy over efficiency to achieve end-to-end outcomes.Topics Include:HackerOne uses ethical hackers and AI to find vulnerabilities before criminalsWhite hat hackers stress test systems to identify security weaknesses proactivelyGenerative AI plays a huge role in HackerOne's security operationsSecurity teams struggle with constant toil of finding and fixing vulnerabilitiesAI helps minimize toil through natural language interfaces and automationBoth good and bad actors have access to generative AI toolsSuccess requires measuring individual task inputs and outputs, not just aggregatesBreaking down workflows into granular tasks reveals measurable AI improvementsHackerOne deployed "Hive," their AI security agent to reduce customer toilInitial focus was on tasks where AI clearly outperformed humansStarted with low-hanging fruit before tackling more complex strategic workflowsAccuracy is the primary success metric, not just efficiency or speedSecurity requires precision; wrong fixes create bigger problems than inefficiencyCustomer acceptance and reduced time to remediation are north star metricsHumans remain the source of truth for validation and feedback loopsBreak down human jobs into granular AI tasks using systems thinkingBuild specific agents for individual tasks rather than entire job rolesKeep humans accountable for end-to-end outcomes to maintain customer trustAWS Bedrock chosen for security, confidentiality, and data separation requirementsMoving from efficiency improvements to entirely new AI-enabled capabilitiesParticipants:Alex Rice – Founder & CTO/CISO, HackerOneFurther Links:HackerOne WebsiteHackerOne on AWS MarketplaceSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Spencer Herrick, Principal AI Product Manager of Asana and Oliver Myers of AWS demonstrate how their integration allows Asana's AI workflows to access enterprise data from Amazon Q Business, enabling seamless cross-application automation and insights.Topics Include:Oliver Myers leads Amazon Q Business go-to-market, Spencer Herrick manages Asana AI products.Session focuses on end user productivity challenges with generative AI technology implementations.End users face technology overload with doubled workplace application usage over five years.Data silos prevent getting maximum value from generative AI across fragmented enterprise systems.Workers spend 53% of time on "work about work" instead of strategic contributions.Ideal experience needs single pane of glass with cross-application insights and actions.Amazon Q Business launched as managed service with 40+ enterprise data connectors.Connectors maintain end-user permissions from source systems for enterprise security compliance.QIndex feature enables ISVs to access Q Business data via API calls.End users get answers enriched with multiple data sources without switching applications.Asana's work graph connects all tasks, projects, and portfolios to company goals.Phase 1 AI focused on narrow solutions like smart status updates.Phase 2 aimed for AI teammate capabilities requiring extensive contextual knowledge.AI Studio launched as no-code workflow automation builder within Asana platform.Q integration allows AI Studio to access cross-application context beyond Asana boundaries.SmartChat enhanced with Q can answer "what should I work on today?" holistically.Users returning from PTO can quickly understand goal risks across data sources.AI Studio workflows automate feature request processing across Asana, Drive, Slack, email.Partnership eliminates silos while maintaining enterprise security and permission controls.Integration creates connected ecosystem enabling true cross-application AI automation and insights.Participants:Spencer Herrick - Principal AI Product Manager, AsanaOliver Myers - Worldwide Head of Business Development, Amazon Web ServicesFurther Links:Asana.comAsana on AWS MarketplaceSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Chief Product Officer Dan Brown explains how Celonis creates digital twins of business processes to power AI agents that automate operational improvements.Topics Include:Dan Brown introduces Celonis as the thought leader in process mining for over a decade.Celonis serves largest global companies across all industries seeking operational improvements.Companies have process diagrams but actual operations differ significantly from documentation.Celonis creates digital twins of business processes by analyzing system data flows.Process intelligence reveals how work actually happens versus how companies think it happens.Platform enables process normalization, improvement assessment, and automated corrective actions.Celonis vision: making processes work better for people, companies, and the planet.Process intelligence provides visibility into current operations and improvement strategies.Great AI requires great data, but most companies only have static views.Process intelligence graph shows real-time flow of orders, invoices, and opportunities.Agentic AI requires four capabilities: sensing, planning, executing, and governing operations.Process intelligence enables real-time detection of conformance problems and deviations.AWS partnership leverages Bedrock for agentic AI and infrastructure for data processing.Data ingestion, organization, and enrichment are core to process intelligence value.AI agents now handle process deviations with increasing autonomy and sophistication.Heavy equipment manufacturer uses agents to coordinate with third-party vendors automatically.Agents text and email vendors to confirm delivery dates, reducing manual work.Implementation challenges include data quality, conservative adoption, and governance concerns.Companies should start with achievable use cases and expand gradually across domains.Future involves enterprise-wide process visibility powering automated applications and continuous improvement.Participants:Dan Brown – Chief Product Officer, CelonisFurther Links:Celonis WebsiteCelonis on AWS MarketplaceSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

AWS partners Automation Anywhere, Qlik, and Vectra.ai discuss revolutionizing customer experience through generative AI, sharing real-world implementations in automation, analytics, and cybersecurity applications. Topics Include:AWS Technology Partnerships panel on agentic AI implementationThree AWS partners share real-world AI deployment experiencesAutomation Anywhere automates end-to-end business processes with agentsVectra.ai uses autonomous agents for cybersecurity threat detectionQlik applies generative AI across their data platform portfolioCustomer service automation handles L1 support requests efficientlyUtility company processes 144,000 complaints annually using agentsRegulatory compliance improved through faster complaint resolution workflowsCybersecurity agents reduce threat detection time by 50-60%Triage, correlation, and prioritization handled by autonomous agentsSignal fatigue reduced through intelligent alert filtering systemsNatural language queries enable faster business decision makingSales AI agent provides competitive information during callsAWS Marketplace reduced 7,000 weekly tickets to zero2023 was proof-of-concept year, 2024 focuses production deploymentAWS Bedrock integration seamless with existing data repositoriesModel optionality crucial for different use case requirementsAgility most important capability in generative AI journeyCode abandonment becomes acceptable due to rapid innovationMaximum team size of 10 people maintains development agilityTargeted solutions outperform broad platform capabilities in adoptionImplementation expertise becomes bottleneck for customer scaling effortsNatural language interaction patterns completely shifted user behaviorKeywords searches replaced by conversational query approachesResponsible AI committees review decisions and establish principlesSecurity considerations balance speed with responsible deployment practicesBad actors adopt generative AI faster than defendersExplainability requirements slow feature rollout but ensure auditabilityMulti-modal deployments use different models for specific casesFuture trends include AI-powered business process outsourcingParticipants:Peter White – SVP, Emerging Products, Automation AnywhereRyan Welsh – Field CTO - Generative AI, QlikJohn Skinner – Vice President Corporate/Business Development, Vectra.aiChris Grusz – Managing Director for Technology Partnerships, AWSFurther Links:Automation Anywhere in AWS MarketplaceQlik in AWS MarketplaceVectra.ai in AWS MarketplaceSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/