AWS for Software Companies Podcast

New Relic's Head of AI and ML Innovation, Camden Swita discusses their four-cornered AI strategy and envisions a future of "agentic orchestration" with specialized agents.Topics Include:Introduction of Camden Swita, Head of AI at New Relic.New Relic invented the observability space for monitoring applications.Started with Java workloads monitoring and APM.Evolved into full-stack observability with infrastructure and browser monitoring.Uses advanced query language (NRQL) with time series database.AI strategy focuses on AI ops for automation.First cornerstone: Intelligent detection capabilities with machine learning.Second cornerstone: Incident response with generative AI assistance.Third cornerstone: Problem management with root cause analysis.Fourth cornerstone: Knowledge management to improve future detection.Initially overwhelmed by "ocean of possibilities" with LLMs.Needed narrow scope and guardrails for measurable progress.Natural language to NRQL translation proved immensely complex.Selecting from thousands of possible events caused accuracy issues.Shifted from "one tool" approach to many specialized tools.Created routing layer to select right tool for each job.Evaluation of NRQL is challenging even when syntactically correct.Implemented multi-stage validation with user confirmation step.AWS partnership involves fine-tuning models for NRQL translation.Using Bedrock to select appropriate models for different tasks.Initially advised prototyping on biggest, best available models.Now recommends considering specialized, targeted models from start.Agent development platforms have improved significantly since beginning.Future focus: "Agentic orchestration" with specialized agents.Envisions agents communicating through APIs without human prompts.Integration with AWS tools like Amazon Q.Industry possibly plateauing in large language model improvements.Increasing focus on inference-time compute in newer models.Context and quality prompts remain crucial despite model advances.Potential pros and cons to inference-time compute approach.Participants:Camden Swita – Head of AI & ML Innovation, Product Management, New RelicSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Jon Yoo, CEO of Suger, shares how his company automates the complex & challenging workflows of selling software through cloud marketplaces like AWS.Topics Include:Jon Yoo is co-founder/CEO of Suger.Suger automates B2B marketplace workflows.Handles listing, contracts, offers, billing for marketplaces like AWS.Co-founder previously led Confluent's marketplace enablement product.Confluent had 40-50% revenue through cloud marketplaces.Required 10-20 engineers working solely on marketplace integration.Engineers prefer core product work over marketplace integration.Product/engineering leaders struggle with marketplace deployment requirements.Marketplace customers adopt without marketing, creating unexpected management needs.Version control is challenging for marketplace-deployed products.License management through marketplace creates engineering challenges.Suger helps sell, resell, co-sell through AWS Marketplace.Marketplace integration isn't one-time; requires ongoing maintenance.Business users constantly request marketplace automation features.Suger works with Snowflake, Intel, and AI startups.Data security concerns drive self-hosted AI deployments.AI products increasingly deploy via AMI/container solutions.AI products use usage-based pricing, not seat-based.Usage-based pricing creates complex billing challenges.AI products are tested at unprecedented rates.Two deployment options: vendor cloud or customer cloud.SaaS requires reporting usage to marketplace APIs.Customer-hosted deployment simplifies some billing aspects.Marketplaces need integration with ERP systems.Version control particularly challenging for AI products.Companies need automated updates for marketplace-deployed products.License management includes scaling up/down and expiration handling.Suger aims to integrate with GitHub for automatic updates.Participants:·        Jon Yoo – CEO and Co-founder, SugerSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/ 

SentinelOne's Ric Smith shares how Purple AI, built on Amazon Bedrock, helps security teams handle increasing threat volumes while facing budget constraints and talent shortages.Topics Include:Introduction of Ric Smith, President of Product Technology and OperationsSentinelOne overview: cybersecurity company focused on endpoint and data securityCustomer range: small businesses to Fortune 10 companiesProducts protect endpoints, cloud environments, and provide enterprise observabilityRic oversees 65% of company operationsPurple AI launched on AWS BedrockPurple AI helps security teams become more efficient and productiveSecurity teams face budget constraints and talent shortagesPurple AI helps teams manage increasing alert volumesTop security challenge: increased malware variants through AIAI enables more convincing spear-phishing attemptsIdentity breaches through social engineering are increasingVoice deepfakes used to bypass security protocolsFuture threats: autonomous AI agents conducting orchestrated attacksSentinelOne helps with productivity and advanced detection capabilitiesSentinelOne primarily deployed on AWS infrastructureUsing SageMaker and Bedrock for AI capabilitiesBest practice: find partners for AI training and deploymentCustomer insight: Purple AI made teams more confident and creativeAI frees security teams from constant anxietySentinelOne's hyper-automation handles cascading remediation tasksMultiple operational modes: fully automated or human-in-the-loopAgent-to-agent interactions expected within 24 monthsCommon misconception: generative AI is infallibleAI helps with "blank slate problem" providing starting frameworksAI content still requires human personalization and reviewAWS partnership provides cost efficiency and governance benefitsParticipants:·        Ric Smith – President – Product, Technology and Operations, SentinelOneSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/ 

Sam Gantner, Chief Product Officer of Nexthink, reveals how DEX is moving IT from reactive firefighting to proactive problem prevention and transforming enterprise productivity.Topics Include:DEX stands for Digital Employee ExperienceDEX eliminates IT issues preventing employee productivityShifts IT from reactive to proactive problem-solvingEmployees often serve as IT problem alerting systemsBest IT is transparent to employeesDEX solves device sluggishness and slow application issuesNetwork problems consistently appear across organizationsIT teams often lack visibility into employee experiencesMany organizations waste money on unused software licensesDEX Score measures comprehensive employee IT experienceSurveys capture subjective aspects of technology experienceReduction of actual problems differs from ticket reductionNexthink uses lightweight agents on employee devicesBrowser monitoring essential as browsers become application platformsEmployee engagement metrics capture real-time feedbackNexthink rebuilt as cloud-native platform using AWS servicesCompany deploys across 10+ global AWS regions30% of engineering resources dedicated to AI developmentOne customer eliminated 50% of IT ticketsAnother recovered 37,000 productivity hours worth $3M annuallyA third saved $1.3M by identifying unused licensesAI implementation requires dedicated employee trainingGood AI now better than perfect AI neverTechnology adoption is the next DEX frontierDigital dexterity becoming critical for maximizing IT investmentsParticipants:Samuele Gantner – Chief Product Officer, NexthinkSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Linda Ivy-Rosser, Vice President for Forrester, outlines the evolution of business applications and forward thinking predictions of their future.Topics Include:Linda Ivy-Rosser has extensive business applications experience since the 1990s.Business applications historically seen as rigid and lethargic.1990s: On-premise software with limited scale and flexibility.2000s: SaaS emergence with Salesforce, AWS, and Azure.2010s: Mobile-first applications focused on accessibility.Present: AI-driven applications characterize the "AI economy."Purpose of applications evolved from basic to complex capabilities.User expectations grew from friendly interfaces to intelligent systems.Four agreements: AI-infused, composable, cloud-native, ecosystem-driven.AI-infused: 69% consider essential/important in vendor selection.Composability expected to grow in importance with API architectures.Cloud-native: 79% view as foundation for digital transformation.Ecosystem-driven: 68% recognize importance of strategic alliances.Challenges: integration, interoperability, data accessibility, user adoption.43% prioritizing cross-functional workflow and data accessibility capabilities.Tech convergence recycles as horizontal strategy for software companies.Data contextualization crucial for employee adoption of intelligent applications.Explainable AI necessary to build trust in recommendations.Case study: 83% of operators rejected AI recommendations without explanations.Tulip example demonstrated three of four agreements successfully.Software giants using strategic alliances as competitive advantage.AWS offers comprehensive AI infrastructure, platforms, models, and services.Salesforce created ecosystem both within and outside their platform.SaaS marketplaces bridge AI model providers and businesses.Innovation requires partnerships between software vendors and ISVs.Enterprises forming cohorts with startups to solve business challenges.Software supply chain transparency increasingly important.Government sector slower to adopt cloud and AI technologies.Change resistance remains significant challenge for adoption.69% prioritize improving innovation capability over next year.Participants:Linda Ivy-Rosser - Vice President, Enterprise Software, IT services and Digital Transformation Executive Portfolio, ForresterSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

New Relic's Chief Customer Officer Arnaldo (Arnie) Lopez details how their observability platform helps 70,000+ customers monitor cloud performance through AWS infrastructure while introducing AI capabilities that simplify operations.Topics Include:Arnie Lopez is SVP, Chief Customer Officer at New Relic.Oversees pre-sales, post-sales, technical support, and enablement teams.New Relic University offers customer certifications.Founded in 2008, pioneered application performance monitoring (APM).Now offers "Observability 3.0" for full-stack visibility.Prevents interruptions during cloud migration and operations.Serves 70,000+ customers across various industries.16,000 enterprise-level paying customers.Platform consolidates multiple monitoring tools into one solution.Helps detect issues before customers experience performance problems.Market challenge: customers using disparate observability solutions.Reduces TCO by eliminating multiple monitoring tools.Targets VPs, CTOs, CIOs, and sometimes CEOs.Decade-long partnership with AWS.Platform built on largest unified telemetry data cloud.Uses AWS Graviton instances and Amazon EKS.AWS partnership enables innovation and customer trust.Three AI approaches: user assistance, LLM monitoring, faster insights.New Relic AI helps write query language (NURCLs).Monitors LLMs in customer environments.Uses AI to accelerate incident resolution.Lesson learned: should have started AI implementation sooner.Many customers still cautiously adopting AI technologies.Goal: continue growth with AWS partnership.Offers compute-based pricing model.Customers only pay for what they use.Announced one-step AWS monitoring for enterprise scale.Amazon Q Business and New Relic AI integration.Agent-to-agent AI eliminates data silos.Embeds performance insights into business application workflows.Participants:Arnie Lopez – SVP Chief Customer Officer, New RelicSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

PDI Technologies’ Steve Antonakakis shares how his company is implementing generative AI across their fuel and retail technology ecosystem through a practical, customer-focused approach using Amazon Bedrock.Topics Include:PDI's COO/CTO discussing generative AI implementationPractical step-by-step approach to AI integrationTesting in real-world settings with customer feedbackAWS Bedrock and Nova models exceeded expectationsEarly adoption phase with huge potentialFuel/retail industry processes many in-person transactionsPDI began in 1983 as ERP providerGrew through 33+ acquisitionsProvides end-to-end fuel industry solutionsOwns GasBuddy and Shell Fuel RewardsProcesses millions of transactions dailyGenerative AI fits into their intelligence plane architectureAWS Bedrock integrates well with existing infrastructureFocus on trusted, controlled, accountable AIProductizing AI features harder than traditional featuresCreated entrepreneurial structure alongside regular product teamsTeam designed to fail fast but stay customer-focusedAI features can access databases without disrupting applicationsCustomers want summarization across different business areasAI provides insights and actionable recommendationsConversational AI replaces traditional reporting limitationsWorking closely with customers to solve problems togetherBeyond prototyping phase, now in implementationAWS Nova provides excellent cost-to-value ratioFocus on measuring customer value over immediate profitabilityRFP use case saved half a million dollarsEarly prompts were massive, now more structuredSetting realistic customer expectations is importantData security approach same as other applicationsTreating AI outputs with same data classification standardsParticipants:Steve Antonakakis – COO & CTO, Retail & Energy, PDI TechnologiesSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

AWS partners Braze, Qualtrics, and Tealium share strategies for marketplace success, vertical industry expansion, and generative AI integration that have driven significant business growth.Topics Include:Jason Warren introduces AWS Business Application Partnerships panel.Three key topics: Marketplace Strategy, Vertical Expansion, Gen-AI Integration.Alex Rees of Braze, Matthew Gray of Tealium, and Jason Mann of Qualtrics join discussion.Braze experienced triple-digit percentage growth through AWS Marketplace.Braze dedicating resources specifically to Marketplace procurement.Tealium accelerated deal velocity by listing on Marketplace.Tealium saw broader use case expansion with AWS co-selling.Qualtrics views Marketplace listing as earning a "diploma."Understanding AWS incentives and metrics is crucial.Knowing AWS "love language" helps partnership success.Braze saw transaction volume increase between Q1 and Q4.Aligning with industry verticals unlocked faster growth.Tealium sees bigger deals and faster close times.Tealium moved from transactional to strategic marketplace approach.Private offers work well for complex enterprise agreements.Qualtrics measures AWS partnership through "influence, intel, introductions."AWS relationships help navigate IT and procurement challenges.Propensity-to-buy data guides AWS engagement strategy.Marketplace strategy evolving with new capabilities and international expansion.Brazilian marketplace distribution reduces currency and tax challenges.Partnership evolution: sell first, then market, then co-innovate.Braze penetrated airline market through AWS Travel & Hospitality.RFP introductions show tangible partnership benefits.Tealium partnering with Virgin Australia and United Airlines.MUFG bank case study shows joint AWS-Tealium success.Qualtrics won awards despite not completing formal competencies.Focus on fewer verticals yields better results.Gen AI brings both opportunities and regulatory concerns.First-party data rights critical for AI implementation.AWS Bedrock integration provides security and prescriptive solutions.Participants:Alex Rees – Director Tech Partnerships, BrazeJason Mann – Global AWS Alliance Lead, QualtricsMatthew Gray - SVP, Partnerships & Alliances, TealiumJason Warren - Head of Business Applications ISV Partnerships (Americas), AWSSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Yashodha Bhavnani, Head of AI at Box, reveals Box's vision for intelligent content management that transforms unstructured data into actionable insights.Topics Include:Yashodha Bhavnani leads AI products at Box.Box's mission: power how the world works together.Box serves customers globally across various industries.Works with majority of Fortune 500 companies.AI agents will join workforce for repetitive tasks.Workflows like hiring will become easily automated with AI.Content will work for users, not vice versa.Customers demand better experiences with generative AI.Box calls this shift "intelligent content management."90% of enterprise content is unstructured data.AI thrives on unstructured data.Current content systems are unproductive and unsecured.AI can generate insights from scattered company knowledge.AI extracts metadata automatically from documents like contracts.Automated workflows triggered by AI-extracted data.Box provides enterprise-grade AI connected to your content.AI follows same permissions as the content itself.Customer data never used to train AI models.AI helps classify sensitive data to prevent leaks.Box offers choice of AI models to customers.AI is seamlessly connected with customer content.Administrators control AI deployment across their organization.Partnership with AWS Bedrock brings frontier models to Box.Box supports customers using their own custom models.Box preparing for AI agents to join workforce.Introduced "AI Units" for flexible pricing.Basic AI included free with Business Plus tiers.Both horizontal and vertical multi-agent architectures planned.Working toward agent-to-agent communication protocols.Participants:Yashodha Bhavnani - VP of Product Management, AI products, BoxSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Tech leaders from RingCentral, Zoom and AWS discuss how generative AI is transforming business communications while balancing challenges & regulatory concerns in this rapidly evolving landscape.Topics Include:Introduction of panel on generative AI's impact on businesses.How to transition AI from prototypes to production.Understanding value creation for customers through AI.Introduction of Khurram Tajji from RingCentral.Introduction of Brendan Ittleson from Zoom.How generative AI fits into Zoom's product offerings.Zoom's AI companion available to all paid customers.Zoom's federated approach to AI model selection.RingCentral's new AI Receptionist (AIR) launch.How AIR routes calls using generative AI capabilities.AI improving customer experience through sentiment analysis.The disproportionate value of real-time AI assistance.Economics of delivering real-time AI capabilities.Real-time AI compliance monitoring in banking.Value of preventing regulatory fines through AI.Voice cloning detection through AI security.Democratizing AI access across Zoom's platform.Monetizing specialized AI solutions for business value.Challenges in taking AI prototypes to production.Importance of selecting the right AI models.Privacy considerations when training AI models.Maintaining quality without using customer data for training.Co-innovation with customers during product development.Scaling challenges for AI businesses.Case study of AI in legal case assessment.Ensuring unit economics work before scaling AI applications.Zoom's approach to scaling AI across products.Importance of centralizing but federating AI capabilities.Breaking down data silos for effective AI context.Navigating evolving regulations around AI.EU AI Act restrictions on emotion inference.Balancing regulations with customer experience needs.Future of AI agents interacting with other agents.How AI enhances human connection by handling routine tasks.Impact of AI on company valuations and M&A activity.Participants:Khurram Tajji – Group CMO & Partnerships, RingCentralBrendan Ittleson – Chief Ecosystem Officer, ZoomSirish Chandrasekaran – VP of Analytics, AWSSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/