AWS for Software Companies Podcast

Avalara's Chief Architect Tim Diekmann reveals how AI and agentic technology are transforming tax compliance and accuracy across 40,000 jurisdictions leveraging AWS.Topics Include:Avalara provides tax compliance software across North America, Europe, and beyond.They operate between commerce and government, covering 40,000+ jurisdictions.Services span registration, sales tax calculation, and certificate management.Avalara was the only company keeping pace with rapid tariff changes.AI is used to parse unstructured documents like tax notices and publications.Intelligent mapping automates ERP integration across vastly different system configurations.GenAI lets customers query billions of transactions using plain conversational language.Avalara and AWS are now engaged in a promising co-selling motion.Time-to-go-live and transaction accuracy are the key success metrics tracked.Amazon Q was rolled out company-wide, achieving 95% developer adoption.AI literacy is now prioritized across legal, HR, and engineering teams alike.Agentic AI will embed Avalara directly inside customer ERP systems going forward.Participants:Tim Diekmann – SVP of Engineering, Chief Architect, AvalaraSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Honeycomb Co-founder and CTO Charity Majors explains why measuring the right engineering metrics in the age of AI matters more than chasing numbers.Topics Include:Charity Majors introduces Honeycomb as the original observability company for complex systemsHoneycomb solves high cardinality problems across millions of individual customer experiencesTheir MCP tool ranked top five in Stack Overflow's most-used listCanva lets developers interact with production software directly from their IDEAI acts as an amplifier requiring strong reliability and observability foundationsMeasuring success requires multiple metrics to avoid gaming single numbersHoneycomb adopted Intercom's 2X productivity challenge enlisting employees to identify gainsWriting code was never the hard part even before generative AI arrivedHoneycomb created AI values prioritizing transparency and emotional safety for employeesStaff tested boundaries on resources and environmental impact prompting honest discussionsHoneycomb acquired Grok and shipped Query Assistant Canvas and MCP productsFuture concerns include AI economics shifting and AI-native developers lacking foundational expertiseParticipants:Charity Majors – Co-Founder/CTO, Honeycomb.ioSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Astronomer's Steven Hillion reveals how OpenAI, Anthropic, Uber, and Lyft use Apache Airflow to orchestrate AI and machine learning pipelines at scale on AWS.Topics Include:Steven Hillion leads data and AI at AstronomerApache Airflow surpassed Spark and Kafka in community metricsAstronomer coordinates data flow like conductor orchestrating instrumental platformsOrganizations with data engineering teams use Airflow at scaleCustomers already used Airflow for ML before official promotionUber and Lyft orchestrate pricing models using AirflowAstronomer runs on AWS with close integration partnershipsOpenAI Anthropic and GitHub Copilot use Airflow for operationsInternal data team uses Airflow creating feedback loopsEvolved from constrained AI reports to agentic workflowsPlatform monitors generative AI output quality at user interactionsMetadata and context increasingly critical for AI applicationsLearn more at Astronomer’s Data FlowCast podcastParticipants:Steven Hillion – SVP, Data and AI, AstronomerSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Learn how Docupace transformed from cloud-native platform to AI-powered wealth tech leader, leveraging AWS partnerships and customer obsession to accelerate growth.Topics Include:Docupace Technologies has served wealth management firms for twenty years.Three SaaS product lines streamline advisor workflows and back offices.AI transforms both customer operations and Docupace's internal business practices.Trust between advisors and investors drives conservative technology adoption approach.Serving seven top-ten broker dealers demands careful data security strategies.AI shifts financial systems from deterministic certainty to probabilistic outcomes.Industry began AI adoption with simple meeting note-taking applications.Docupace's agentic AI framework enables safe, observable, orchestrated agent deployment.Multiple verification layers and human oversight ensure zero-error financial operations.Internal AI implementation required nine months navigating change management hurdles.Team curiosity and rapid experimentation matter more than traditional skill sets.AWS customer obsession and partnership programs dramatically accelerate business growth.Participants:Michael Pinsker – Founder and President, Docupace TechnologiesSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Boomi CEO Steve Lucas reveals how to flip AI's 95% failure rate to your favour with practical integration strategies, real-world agent deployments, and an AWS partnership.Topics Include:Boomi solves the forever problem of complexity across applications and systemsTwenty-five thousand customers use Boomi to automate anything and connect everythingBoomi moves more data per second than the entire Visa networkAI agents now integrate systems through simple commands, no coding requiredAgentic platform built with AWS creates custom AI agents in real timeUse cases include expense monitoring and heart defibrillator battery checks dailyAutomotive companies use AI agents to assess tariff risks across supply chainsHospitals deploy agents to detect patient falls and alert medical professionals immediatelyControl Tower co-innovated with AWS monitors and manages all AI agents centrallyDeterministic processes like payroll shouldn't use AI, probabilistic challenges shouldNinety-five percent of AI projects fail due to data access problemsAgentic workshops help companies identify high-ROI opportunities and achieve AI successParticipants:Steve Lucas – Chairman & CEO, BoomiSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Fabric CTO Ankush Goyal reveals how AI Search is transforming commerce discovery and why merchants need AI agents to compete effectively.Topics Include:Fabric builds AI agents for commerce, solving merchant visibility challengesCommerce shifting due to AI Search channels and smaller retail teamsProduct Agent monitors and improves product visibility across AI channelsPetMeds uses Fabric to optimize AI Search and automate SKU onboardingFabric evolved from commerce platform company to AI agent solutionsAgentic and generative AI work together to optimize product catalogsFabric uses AWS EKS, Bedrock, S3, and Nova models heavilyAWS partnership connects Fabric with industry leaders and growth opportunitiesAWS services enable reliable, cost-effective, and performant enterprise AI agentsPrototyping agents is easy, but enterprise-grade reliability is extremely challengingFour key learnings: workflow reliability, context engineering, cost effectiveness, feedback loopsCTOs should define agent goals, guardrails, context, and evaluations earlyLong-running workflow durability and snapshots prevent costly repeated work failuresFuture innovations focus on specialized models, retrieval frameworks, automated evaluationsMerchants can evaluate AI Search performance at fabric.inc or LinkedInParticipants:Ankush Goyal – Chief Technology Officer, FabricSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Abrigo's Chief Product Technology Officer reveals how they're leveling the playing field for 2,400 community banks using AWS-powered AI to compete with billion-dollar financial institutions.Topics Include:Abrigo serves 2,400 community banks and credit unions across the USThey provide risk management, fraud detection, and digital loan origination solutionsConnect platform delivers data analytics for institutions with legacy systemsCommunity banks need instant digital experiences to compete with fintech upstartsCustomers expect Uber-like speed from application to cash within hoursThree technology waves transformed finance: iPhone, cloud computing, then AIChatGPT changed conversational experiences and knowledge search expectations in bankingAI enables instant policy search for new employee onboarding needsEvery minute saved from grunt work gets redeployed into customer relationshipsSimple borrower experiences work across all demographics from boomers to millennialsAbrigo embraced agentic AI early using AWS Bedrock and Agent CoreNew guardrails and evaluations accelerate deterministic workflow reimagination with agentsParticipants:Ravikumar Nemalikanti – Chief Product and Technology Officer, AbrigoSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Hear how Halo manages market disruption and technology innovation with their unique culture, helping them scale to be a leader in workflow automation software.Topics Include:Halo serves 125,000 teams across 75 countries with enterprise ITSM solutionsPaul Hamilton founded company 21 years ago as freelance IT consultantBuilt ticketing software to track their own freelance client work originallyNo marketing budget so mastered organic SEO without paid advertising spendReached number one Google ranking globally for help desk software 2006Hired first employee in 2011 when co-founder wanted outAWS partnership began years ago recognizing trajectory not current snapshot sizeAWS team proactively delivered 20 percent infrastructure optimization cost savings recentlyHalo reducing prices using savings for customer value creationHires graduates and trains them rather than poaching experienced enterprise talentMonday morning all-company meetings ensure transparency with minimal management hierarchy levelsNo traditional sales teams, culture emphasizes autonomy and employee ownership stakesTechnology completely rebuilt 2017-2018 delivering deployments in one-third typical timeframesTotal cost ownership 70 percent lower than competitors while winning tendersVision transcends software through music festivals, documentaries pioneering fulfilling workplace cultureParticipants:Paul Hamilton – CEO and Founder, HaloAlison Kay – Vice President / Managing Director, AWS UKISee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Neo4j's Ajay Singh discusses future shifts in AI and why knowledge graphs may be the missing layer in your Gen AI strategy.Topics Include:Ajay Singh from Neo4j discusses graph intelligence platform serving 80+ Fortune 100 companies.Financial services firms use Neo4j knowledge graphs to detect fraud rings and accounts.IT companies build digital twins of infrastructure to analyze attack surfaces and vulnerabilities.Knowledge graphs provide richer context for Gen AI agents beyond what vector search offers.Gaming company achieved 10x faster insights and 92% reduction in analyst data gathering.Transportation company improved tariff code workflow from 50% abandonment to 95% completion rate.Neo4j has partnered with AWS since 2013, running on AWS infrastructure and Marketplace.Customers combine Neo4j with AWS Bedrock and SageMaker to build agentic AI applications.Neo4j evolved from late-stage AWS collaboration to early-stage joint customer solution development approach.Success requires business-first mindset over technology-first to avoid POCs that never reach production.Effective Gen AI needs semantic layers and knowledge graphs, not just throwing documents at LLMs.Future agents will tackle outcome-based objectives requiring explainability, security, and proper LLM operations.Participants:Ajay Singh – Global Vice President, Neo4jSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Executives from March Networks explain how Amazon Bedrock transformed petabytes of surveillance video into economically viable solutions that unlock untapped business value.Topics Include:March Networks CEO and CPO discuss video surveillance for enterprise banks and retailers globallyCompany serves 10,000 customers with 250,000 installations worldwide since 2003 from Ottawa headquartersBanking customer operates across 25 countries centralizing video operations on one standardized platformSingle enterprise customer manages 65 petabytes of distributed data across March Networks recordersAWS partnership enables five-to-ten-year cloud transition starting with economical DeepGlacier storage solutionsAmazon Bedrock powers AI Smart Search analyzing snapshots for searchable business intelligence insightsEnterprise video data remains largely untapped for retail traffic patterns and operational efficiencyOne retailer processes three million daily POS transactions across 6,000 locations synchronized with video2025 brought AI Smart Search launch enabling natural language queries across entire operationsCloud storage became economically viable using Glacier after traditional quotes reached millions annuallyFraudsters exploit 90-180 day retention windows by waiting six months to file lawsuits2026 vision emphasizes consultative selling for efficiency gains supported by strong AWS partnershipParticipants:Peter Strom – President & Chief Executive Officer, March NetworksJeff Corrall – Chief Product Officer, March NetworksSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Anthropic's Tobias Harrison Noonan shares the enterprise AI playbook: why coding leads to broader AI adoption, practical tips for getting started, and why you shouldn't wait for perfection.Topics Include:Tobias from Anthropic's Applied AI team discusses enterprise AI adoption trends and insights.Anthropic founded four years ago balancing AI safety mission with world's most intelligent models.Remarkable velocity: Claude 3.7 and Claude Code both shipped just in 2025 alone.Three-layer partnership: foundation models, enterprise capabilities, and end-user platforms like Claude Code.Anthropic leads in agentic coding for eighteen months, now number one enterprise AI market share.Claude Opus 4.5 launched last week, again tops software engineering benchmark for complex tasks.Claude Code enables thirty-hour autonomous coding sessions, ships features five times faster than before.Next frontier expands beyond coding into data-heavy knowledge work like financial and legal analysis.AI adoption maturity curve: employee workflows, internal processes, core products, then AI-native products.Thomson Reuters started with Claude Code for development team doing code modernization and refactoring.They expanded to Claude.ai for sales, marketing, and finance teams after seeing tangible ROI.Built Claude into core products including co-counsel legal platform and fraud prevention systems strategically.Today Thomson Reuters has eight different product lines powered by Claude across their portfolio.AWS partnership offers safe, secure, scalable deployment from POC to production in existing environments.Don't wait for perfection: AI today is dumbest it'll ever be, start prototyping now.Participants:Tobias Harrison-Noonan: Member of Technical Staff, AnthropicSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Straight from re:Invent 2025, technology leaders from C3 AI, nCino, New Relic and Vercel reveal learnings, best practices and predictions for the future of Agentic AI.Topics Include:Four technology executives introduce their companies' AI innovations in fintech, cloud, enterprise software, and observability.Vercel built agents for code reviews, infrastructure optimization, and across finance, sales, and support functions.C3.ai deploys enterprise AI applications from scratch to production in six months for Fortune 500s.New Relic provides observability for AI systems and built agents that resolve infrastructure issues in real-time.Vercel's agents improve code quality by incorporating security and framework best practices into AI-generated output.C3.ai partnered with Department of Defense to autonomously produce mission-critical intelligence assessment reports from data.Industry shifted from copilots everywhere to agents that actually own outcomes and land the plane.New Relic moved beyond natural language translation to agents that execute actions and resolve issues autonomously.Panel debates whether Model Context Protocol or broader ecosystem approaches better enable agent interoperability and communication.Autonomy requires accountability: agent decisions must be explainable with traceable steps and replay capabilities built-in.Governance and security should be prerequisites for acceleration, not impediments—a critical mental model shift needed.Many enterprises struggle with process bottlenecks preventing them from harnessing high-quality agents despite having technology.Financial services must carefully balance where human discretion remains essential versus where agent autonomy justified.Will Jung envisions deeply continuous context enabling banks to deliver truly personalized insights without appearing creepy.Suraj Krishnan predicts agents will own outcomes by 2026, coordinating tools and other agents to achieve goals.Participants:Panelist: Merel Witteveen, SVP of Operations, C3.aiPanelist: Will Jung, Chief Technology Officer, nCinoPanelist: Suraj Krishnan, GVP of Engineering, New RelicPanelist: Aparna Sinha, Senior Vice President, Product, VercelModerator: Olawale Oladehin, Managing Director, NAMER Technology Segments (Enterprise, ISV, DNB, and Model Providers), 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/

Four enterprise AI leaders from Box, Snorkel AI, Sumo Logic, and Talkdesk peel away the hype and share battle-tested strategies for implementing agentic AI at scale.Topics Include:Carol Potts introduces panel featuring AI leaders from Box, Snorkel AI, Sumo Logic, and TalkdeskDiego Dugatkin explains Box serves 120,000 enterprise customers with 1.5 exabytes of secure cloud contentKui Jia shares Sumo Logic processes petabytes daily across 10 AWS regions for intelligent operationsYunjing Ma describes Talkdesk's evolution from contact center to customer experience automation through agentic AIDennis Panos positions Snorkel AI as leader in embedding human knowledge into data-centric applicationsDiego reveals Box uses AI internally for faster development and externally for metadata extraction automationKui explains security teams face overwhelming volumes, sometimes 1,000 signals daily, many AI-generated attacksSumo Logic announces SOC analyst agent in customer beta and query agent in general availabilityYunjing details Talkdesk's multi-agent hierarchy architecture powered by unified TalkDesk Data Cloud platformFour key areas identified: discovery of opportunities, building knowledge-powered agents, optimization, and measurementDennis emphasizes starting with trusted data foundation before adding generative AI capabilities to avoid hallucinationsDiego stresses governance importance: AI guardrails plus traditional data security create comprehensive protection frameworkKui warns POC-to-production gap requires intentional design: different latency, accuracy, and security requirements at scaleYunjing shares customer success: 80,000 daily calls, 11,000 documents, 97% accuracy despite complex compliance rulesKey success factors include prompt engineering optimization and real-time data processing mechanism improvementsDiego advises learning AI tools end-to-end: from ideation through functional demos without traditional prototyping delaysDennis recommends robust evaluation frameworks across system components, similar to software unit testing approachesYunjing reinforces data processing optimization and governance remain essential alongside exciting agentic AI capabilitiesKui urges immediate action: technology evolves rapidly, perfect solutions don't exist, customer focus builds trustFinal advice centers on treating AI as digital teammate, not replacement, enhancing productivity and creativityPlatform partnerships like AWS Bedrock solve heavy lifting, allowing teams to focus on core differentiatorsParticipants:Diego Dugatkin - Chief Product Officer, BoxDennis Panos - Head of Enterprise AI, SnorkelAIKui Jia - VP AI Engineering, Sumo LogicYunjing Ma - VP of Engineering, AI, TalkdeskModerator: Carol Potts - General Manager, ISV Sales Segment, North America, 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/

Rubrik's GM of AI Dev Rishi, explains how 85% of enterprises are building agentic AI but lack frameworks to govern agents with production system access - and how Rubrik solves this gap!Topics Include:Dev Rishi explains Rubrik's evolution from data backup to cyber resilience company.Rubrik shifted focus after 2018 when ransomware became the primary business continuity threat.Recent investments center on AI features and security for enterprise data infrastructure.Rubrik's foundation understands organizational data, metadata, and identity access across all systems.Predabase acquisition brought generative AI and LLM platform capabilities into Rubrik's infrastructure.Rubrik Agent Cloud launched to address enterprise AI security and governance needs.180 enterprise conversations revealed AI risk frameworks block ROI, not technology challenges.Agents enable 10x productivity but create 10x damage potential in shorter timeframes.Most organizations struggle enforcing AI policies across AWS Bedrock, OpenAI, and third-party platforms.Agent Undo feature recovers from destructive AI actions using healthy backup snapshots.Three pillars for AI security: define policies, enforce across platforms, enable recovery.2026 will see enterprises shift from pilot agents to managing dozens in production.Participants:Dev Rishi – General Manager of AI, RubrikConnect with Rubrik and learn more here: https://www.rubrik.com/lp/events-hubSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Matt Yanchyshyn, AWS Marketplace and Partner Services VP, reveals how AI agents are transforming enterprises worldwide while Atlassian and Netskope leaders share strategies for scaling up Agentic AI marketplace deals.Topics Include:Matt Yanchyshyn of AWS opens with massive shift to multi-agent production systemsEnterprise software seeing huge AI adoption: 33% will include AI by year endAutomated agents now handle Matt's daily workflow, prioritizing emails and messages autonomouslyReal business transformation across financial reporting, demand forecasting, and automated incident managementAWS Marketplace team productivity up 31%, deploying software 27% faster with agentsNew agent mode for Marketplace uses autonomous data collection improving customer experiencesSuccess requires proper data governance with fine-grained access controls for safe operationsQ Developer and Qiro CLI integrate seamlessly into developer workflows without disruptionAWS maintains 400+ MCP servers, shared spec farms enabling teams to collaborate effectivelyEmbedded experts and principal engineers spread agent knowledge and measure productivity closelyAndy Horwitz notes security leads Marketplace growth, primarily through private offer expansionNetskope's new DSPM product addresses AI data security, driving strong customer adoption momentumEnterprise customers now ask if vendors are AWS badged, deals 41-58% largerAndy advises ISVs: prepare sales teams thoroughly, focus co-sell, secure executive buy-inBill Hustad emphasizes distinct marketplace strategy, seller training, and ruthless operational tracking for successParticipants:Bill Hustad - Global Head of Channel and GTM Ecosystems, AtlassianAndy Horwitz – SVP, Global Partner Ecosystems, NetskopeMatt Yanchyshyn – VP, AWS Marketplace & Partner Services, 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/

Raviteja Yelamanchili shares how Scale AI transformed banking cycles from one year to real-time and why your most valuable enterprise data isn't being collected.Topics Include:Scale evolved from data annotations company to enterprise AI solutions providerHealthcare system transformed patient transcriptions into value using reinforcement learning researchBlank slate customer problems allow Scale to experiment with latest methodsMany customers propose solutions before explaining their actual underlying business problemsBiggest AI misconception: technology will replace jobs rather than augment productivityDon't wait for perfect AI—start learning through iteration and evolution nowBanking credit cycle transformed from one-year process to real-time strategic insightsScale deploys flexibly across EC2, EKS, or Bedrock based on customer requirementsEnterprises want business value generation more than academic research papers aloneNext 12-24 months focus: making data consumable and leveraging unused datasetsTribal knowledge from experienced SMEs represents most valuable yet uncollected dataAgent-based learning captures expertise through feedback loops on Scale's SGP platformParticipants:Raviteja Yelamanchili - Head of Solution Engineering, Scale AISee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

In a keynote address from re:Invent, McKinsey & Company's Lareina Yee shares fascinating data, trends and best practices on AI adoption, the future of skillsets, and leadership insights that are needed for AI transformation at scale.Topics Include:Over 80% of companies have adopted AI in at least one business function currently.Despite heavy investment, 62% of companies remain in experimental or pilot phases with AI.Only 7% of organizations have achieved full-scale AI implementation, up from 2% earlier this year.Agentic AI has proliferated rapidly across functions from knowledge management to manufacturing in one year.Between 45% and 5% of companies have implemented AI agents across different business functions today.AI's productivity potential represents $4.4 trillion in economic value beyond just cost savings opportunities.Innovation ranks as the number one goal for AI investments, ahead of cost reduction priorities.Employee satisfaction, customer satisfaction, and competitive differentiation drive AI adoption alongside revenue growth and cost.High AI performers view implementation as total enterprise transformation, not just technology deployment projects.Leading companies spend 4.9 times more budget on AI investments compared to average performing organizations.Traditional software stacks evolved to SaaS, now transforming into AI-ready tech stacks within one generation.Job outlook remains mixed: 32% expect losses, 13% expect increases, 43% see no major change.Since 2023, significant skill shifts show increased demand for software development and business intelligence capabilities.AI fluency has increased seven times as the most sought-after skill across all job types.AI fluency means using AI in everyday work, not building models or creating large language models.Skills like driving records, coaching, customer service, and management remain harder to automate with current AI.Transactional, data-driven repetitive tasks like inventory management and invoicing face highest automation exposure currently.Historical technology revolutions like electricity created six to eight jobs for every one job displaced.New roles like prompt engineering emerge, requiring skills like effective questioning rather than technical coding.Participants:Lareina Yee - Director of Technology Research, McKinsey & CompanySee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

AWS Principal Solutions Architect Wallace Printz explains how agents are reshaping SaaS business models, pricing strategies, and technical architectures.Topics Include:Wallace Printz discusses agentic workloads transforming SaaS with largest AWS customersNew interaction models include generative UI, voice agents, and proactive workAgents extending SaaS products to interact with external systems and businessesVirtual teammates enabling cross-department collaboration and upskilling non-expert users effectivelyMonetization strategies evolving as predictable costs become variable with agentsThree patterns: dedicated agents, shared agents, and multi-tenant personalized agentsMulti-tenant agents enable hyper-personalized experiences using individual tenant context enrichmentAgent-centric business strategy requires real assessment beyond AI hype cycleAgent orchestration complexity grows with multiple specialized agents interacting togetherTenant isolation requires JWT tokens and AWS Bedrock Agent Core identityCost-per-tenant management needs LLM throttling, tiering, and unified control planeMulti-tenancy creates sticky personalized experiences; AWS white paper releasing soonParticipants:Wallace Printz - Principal Solution Architect, 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/

Industry leaders from Boomi, Demandbase and Smarsh share hard-won lessons on balancing AI creativity with guardrails, why data quality trumps frameworks, and deploying AI at scale.Topics Include:Three industry leaders share experiences building AI solutions at Boomi, Demandbase, and Smarsh.Smarsh manages trillion communications for financial services, detecting bad actors across multiple channels.Boomi built agent studio, garden, and control tower while spawning 33,000 internal agents.Chris Timmerman used vibe coding to build embeddable Boomi in five months solo.Companies balance creativity with guardrails, starting with IT policies before unleashing innovation.Internal adoption driven by empowering teams to build their own solutions versus top-down.Demandbase saw 70% adoption within six months through grassroots approach and local champions.Measuring success proves challenging, comparable to tracking Excel usage rather than specific KPIs.Companies focus on outcomes like touch-free bug fixes and support metrics versus raw usage.Biggest lesson: Data quality and context determine success more than agentic frameworks.Need scaling framework from low-risk UX improvements to high-risk automation with appropriate guardrails.Industry created fatigue by overpromising; should have started smaller with realistic expectations.Participants:Chris Timmerman – Vice President, Global Services Delivery, BoomiHarshal Dedhia – Vice President of AI, DemandbaseBrandon Carl - Executive Vice President of AI and Product Strategy, SmarshAllison Johnson - AMER Technology Partnerships Leader, 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/

Phill Robinson of Boardwave joins Miguel Alava and Massimo Ghislandi of AWS to share research and actionable strategies for European software companies using cloud infrastructure, AI features, and marketplace leverage to drive unprecedented growth.Topics Include:Boardwave and AWS reveal research on European software companies becoming global innovators.Cloud-first businesses exceed customer expectations at 60% versus 46% for laggards.Boardwave's 2,500 CEO members validate findings: AI companies growing 45% annually.Leaders excel at gathering customer feedback for innovation and implementing AI.Top performers leverage marketplaces and deliver continuous customer experience updates consistently.Cloud adoption is foundational for generative AI and agentic AI to scale.Companies face different challenges depending on their cloud maturity stage currently.Cloud serves as table stakes before companies can capture AI growth opportunities.Benchmarking tool helps identify current position and plan strategic next steps forward.Startups should solve universal problems globally, building painkillers not vitamin products.Intercom scales customer service; Wix transforms efficiency through cultural and engineering mindset.Future requires cloud foundation with AI features; AWS offers comprehensive support programs.Participants:Phill Robinson – Chair & Co-Founder, BoardwaveMiguel Alava – EMEA ISV General Manager, Amazon Web ServicesMassimo Ghislandi -  Head of EMEA Marketing for Software Companies, 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/