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 customers
• Cloud-native security platform delivers 100% visibility across enterprise environments at scale
• Customers like Dropbox and Coinbase successfully replaced Splunk with Panther's solution
• Platform processes petabytes monthly with impressive 2.3-minute average threat detection time
• Critical gap identified: alert resolution still takes 8 hours despite fast detection
• Security teams overwhelmed by growing attack surfaces and severe talent burnout
• Constant context switching across tools creates inefficiency and organizational collaboration problems
• AI integration with Amazon Bedrock designed to accelerate security team decision-making
• Four trust principles: verifiable actions, secure design, human control, customer data ownership
• Results 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/

AWS executives reveal how generative AI is fundamentally reshaping ISV business models, from pricing strategies to go-to-market approaches, and provide actionable insights for software companies navigating this transformation.

Topics Include:

• Alayna Broaderson and Andy Perkins introduce AWS Infrastructure Partnerships and ISV Sales
• Generative AI profoundly changing how ISVs build, deliver and market software products
• Two ISV categories emerging: established SaaS companies versus pure gen AI startups
• Legacy SaaS firms struggle with infrastructure modernization and potential revenue cannibalization
• Pure gen AI companies face scaling challenges, reliability issues and cost optimization
• Revenue models shifting from subscription-based to consumption-based pricing per token/prompt/task
• Future-proofing architecture critical as technology evolves rapidly like F-35 fighter jets
• Data becoming key differentiator, especially domain-specific datasets in healthcare and legal
• Balancing cost, accuracy, latency and customer experience creates complex optimization challenges
• Multiple specialized models replacing single solutions, with agentic AI accelerating this trend
• Human capital challenges include retraining engineering teams and finding expensive AI talent
• Security, compliance and explainability now mandatory - no more black box solutions
• Enterprise customers struggle with data organization and quantifying clear gen AI ROI
• ISV pricing models evolving with tiered structures and targeted vertical use cases
• Traditional SaaS playbooks failing in generative AI landscape due to ROI uncertainty
• POC-based go-to-market with free trials and case study selling proving most effective
• Pricing strategies include AI gates, credit systems and separate SKUs for services
• Customer trust requires proactive security messaging and auditable, transparent AI solutions
• Modular architecture enables evolution as new technologies emerge in fast-changing market
• AWS positioning as ultimate gen AI toolkit partner with ISV collaboration opportunities

Participants:

• Alayna Broaderson - Sr Manager, Infrastructure Technology Partnership, Amazon Web Services
• Andy Perkins - General Manager, US ISV, Amazon Web Services

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Hear how PagerDuty and Zoom built successful AI products using Amazon Q-Index to solve real customer problems like incident response and meeting intelligence, while sharing practical lessons from their early adoption journey.

Topics Include:

• David Gordon introduces AWS Q-Business partnerships with PagerDuty and Zoom
• Meet Everaldo Aguiar: PagerDuty's Applied AI leader with academia and enterprise background
• Paul Magnaghi from Zoom brings AI platform scaling experience from Seattle
• Q-Business launched over a year ago as managed generative AI service
• Platform enables agentic experiences: content discovery, analysis, and process automation
• Built on AWS Bedrock with enterprise guardrails and data source integration
• Partners wanted backend capabilities but preferred their own UI and models
• Q-Index provides vector database functionality for ISV partner integrations
• Everaldo explains PagerDuty's evolution from traditional ML to generative AI solutions
• Historical challenges: alert fatigue, noise reduction using machine learning approaches
• New gen AI opportunities: incident context, relevant data surfacing, automated postmortems
• Engineering teams faced learning curve with agents and high-latency user experiences
• Paul discusses Zoom's existing AI: virtual backgrounds and voice isolation technology
• AI Companion strategy focused on simplicity during complex generative AI adoption
• Problem identified: valuable meeting conversations disappear after Zoom calls end
• Customer feedback revealed need for enterprise data integration beyond basic summaries
• Goal: combine unstructured conversations with structured enterprise data seamlessly
• PagerDuty Advanced provides agentic AI for on-call engineers during incidents
• Q-Index integration accesses internal documentation: Confluence pages, runbooks, procedures
• Demo shows Slack integration pulling relevant incident response documentation automatically
• Access control lists ensure users see only data they're authorized to access
• Zoom's AI companion panel enables real-time meeting questions and summaries
• Example use cases: decision tracking, incident analysis, action item identification
• Advice for starting: standardize practices and create internal development templates
• Single data access point reduces legal and security evaluation overhead
• Center of excellence approach helps teams move quickly across product divisions
• Cut through generative AI buzzwords to focus on real user value
• Federated AWS Bedrock architecture provides model choice and flexibility meeting customers
• Customer trust alignment between Zoom conversations and AWS data handling
• Getting started: PagerDuty Advance available now, Zoom AI free with paid add-ons

Participants:

• Everaldo Aguiar – Senior Engineering Manager, Applied AI, PagerDuty
• Paul Magnaghi – Head of AI & ISV Go To Market, Zoom
• David Gordon - Global Business Development, Amazon Q for Business. Amazon Web Services

Further Links:

• PagerDuty Website, LinkedIn & AWS Marketplace
• Zoom 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/

Teleport Co-Founder and CEO Ev Kontsevoy discusses the security vs productivity trade-off that plagues growing companies and how Teleport's trusted computing model protects against the exponential growth of cybersecurity threats.

Topics Include:

• Teleport CEO explains how to make infrastructure "nearly unhackable" through trusted computing
• Traditional security vs productivity trade-off: high security kills team efficiency
• Companies buy every security solution but still get told they're at risk
• Why "crown jewels" thinking fails: computers should protect everything at scale
• Modern infrastructure has too many access paths to enumerate and secure
• Apple's PCC specification shows trusted computing working in real production environments
• AI revolutionizes both offensive and defensive cybersecurity capabilities for everyone
• 80% of companies can't guarantee they've removed all ex-employee access
• Identity fragmentation across systems creates anonymous relationships and security gaps
• Human error probability grows exponentially as companies scale in three dimensions
• Your laptop already demonstrates trusted computing: seamless access without constant logins
• Apple ecosystem shows device trust at scale through secure enclaves
• AI agents need trusted identities just like humans and machines
• AWS marketplace partnership accelerates deals and provides strategic account insights
• Hire someone who understands partnership dynamics before starting with AWS
• Generative AI will make identity attacks cheaper and faster than ever
• Security responsibility shifting from IT teams to platform engineering teams
• Teleport's "steady state invariant": infrastructure locked down except during authorized work
• Temporary access granted through tickets, then automatically revoked after completion
• Legacy systems and IoT devices require extending trust models beyond cloud-native

Participants:

• Ev Kontsevoy – Co-Founder and CEO, Teleport

Further Links:

• Teleport Website
• Teleport 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/

Raj Koo, CTO of DTEX Systems, discusses how their enterprise-grade generative AI platform detects and disarms insider threats and enables them to stay ahead of evolving risks.

Topics Include:

• Raj Koo, CTO of DTEX Systems, joins from Adelaide to discuss insider threat detection
• DTEX evolved from Adelaide startup to Bay Area headquarters, serving Fortune 500 companies
• Company specializes in understanding human behavior and intention behind insider threats
• Market shifting beyond cyber indicators to focus on behavioral analysis and detection
• Recent case: US citizen sold identity to North Korean DPRK IT workers
• Foreign entities used stolen credentials to infiltrate American companies undetected
• DTEX's behavioral detection systems helped identify this sophisticated identity theft operation
• Generative AI becomes double-edged sword - used by both threat actors and defenders
• Bad actors use AI for fake resumes and deepfake interviews
• DTEX uses traditional machine learning for risk modeling, GenAI for analyst interpretation
• Goal is empowering security analysts to work faster, not replacing human expertise
• AWS GenAI Innovation Center helped develop guardrails and usage boundaries for enterprise
• Challenge: enterprises must follow rules while hackers operate without ethical constraints
• DTEX gains advantage through proprietary datasets unavailable to public AI models
• AWS Bedrock partnership enables private, co-located language models for data security
• Private preview launched February 2024 with AWS Innovation Center acceleration support
• Software leaders should prioritize privacy-by-design from day one of GenAI adoption
• Future threat: information sharing shifts from files to AI-powered data queries
• Monitoring who asks what questions of AI systems becomes critical security concern
• DTEX contributes to OpenSearch development while building vector databases for analysis

Participants:

• Rajan Koo – Chief Technology Officer, DTEX Systems

Further Links:

• DTEX Systems Website
• DTEX Systems 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/

Enterprise AI leaders from C3 AI, Resolve AI, and Scale AI reveal how Fortune 100 companies are successfully scaling agentic AI from pilots to production and share secrets for successful AI transformation.

Topics Include:

• Panel introduces three AI leaders from Resolve AI, C3 AI, and Scale AI
• Resolve AI builds autonomous site reliability engineers for production incident response
• C3 AI provides full-stack platform for developing enterprise agentic AI workflows
• Scale AI helps Fortune 100 companies adopt agents with private data integration
• Moving from AI pilots to production requires custom solutions, not shrink-wrap software
• Success demands working directly with customers to understand their specific workflows
• All enterprise AI solutions need well-curated access to internal data and resources
• Software engineering has permanently shifted to agentic coding with no going back
• AI agents rapidly improving in reasoning, tool use, and contextual understanding
• Industry moving from simple co-pilots to agents solving complex multi-step problems
• Spiros coins new concept: evolving from "systems of record" to "systems of knowledge"
• Democratized development platforms let enterprises declare their own agent workflows
• Semantic business layers enable agents to understand domain-specific enterprise operations
• Trust and observability remain major barriers to enterprise agent adoption
• Oversight layers essential for agents making longer-horizon autonomous business decisions
• Performance tracking and calibration systems needed like MLOps for reasoning chains
• CEO-level top-down support required for successful AI transformation initiatives
• Traditional per-seat SaaS pricing models completely broken for agentic AI solutions
• Industry shifting toward outcome-based and work-completion pricing models instead
• Real examples shared: agent collaboration in production engineering and sales automation

Participants:

• Nikhil Krishnan – SVP & Chief Technology Officer, Data Science, C3 AI
• Spiros Xanthos – Founder and CEO, Resolve AI
• Vijay Karunamurthy – Head of Engineering, Product and Design / Field Chief Technology Officer, Scale AI
• Andy Perkins – GM, US ISV Sales – Data, Analytics, GenAI, Amazon Web Services

Further Links:

• C3 – Website – AWS Marketplace
• Resolve AI – Website – AWS Marketplace
• Scale AI – 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/

Industry leaders from Automation Anywhere and AWS discuss how modern customer data collection has evolved, and practical strategies for implementing enterprise automation at scale.

Topics Include:

• Automation Anywhere and AWS experts discuss modern enterprise automation strategies
• Traditional profiting strategies may not work with today's changing business models
• Customer data collection methods have evolved across multiple platforms significantly
• Modern verification processes include automated validation systems and streamlined timelines
• Background check automation is increasingly handled by AI-powered models and systems
• Stanford's "Wonder Bread" research paper introduced revolutionary enterprise process observation technology
• Wonder Bread demonstrated AI systems watching and automatically learning hospital workflows
• The technology can author workflows by observing real enterprise processes
• Enterprise Process Management built around observed behaviors shows promising results
• Verification challenges exist since Wonder Bread research isn't widely publicized yet
• Process observation technology could transform how enterprises handle workflow creation
• Salesforce Wizard Interface dominates many current automation implementations in enterprises
• Salesforce Agent Codes offer alternative approaches to traditional automation methods
• AWS platform selection involves careful consideration of enterprise integration needs
• Demo implementations showcase real-world timeline expectations and deployment maturity levels
• Current automation solutions have reached significant scale across various industries
• Workflow automation differs fundamentally from true agentic intelligence systems capabilities
• Agentic AI demonstrates autonomous decision-making beyond simple rule-based automation processes
• Understanding this distinction helps organizations choose appropriate technology approaches effectively
• Session concludes with clarity on modern automation landscape and implementation strategies

Participants:

• Pratyush Garikapati – Director of Products, Automation Anywhere
• Sreenath Gotur – Snr Generative AI Specialist, Amazon Web Services

Further Links:

• Automation Anywhere website
• Automation Anywhere – 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/

AWS's Mark Relph draws fascinating parallels between today's AI revolution and the 1900s agricultural mechanization that delivered 2,000% productivity gains, while exploring how agentic AI will fundamentally reshape every aspect of software business models.

Topics Include:

• Mark Relph directs AWS's data and AI partner go-to-market strategy team
• His role focuses on making ISV partners a force multiplier for customer success
• Previously ran go-to-market for Amazon Bedrock, AWS's fastest growing service ever
• Current AI adoption pace exceeds even the early cloud computing boom years
• Historical parallel: 1900s agricultural mechanization delivered 2,000% productivity gains and 95% resource reduction
• First commercial self-propelled farming equipment revolutionized entire economies and never looked back
• 500 machines formed the "Harvest Brigade" during WWII, harvesting from Texas to Canada
• Mark has spoken to 600+ AWS customers about GenAI over two years
• Organizations range from AI pioneers to those still "fending off pirates" internally
• GenAI has become a phenomenal assistant within organizations for content and automation
• AWS's AI stack has three layers: infrastructure, Bedrock, and applications
• Bottom layer provides complete control over training, inference, and custom applications
• Middle layer Bedrock serves as the "operating system" for generative AI applications
• Top layer offers ready-to-use AI through Q assistants and productivity tools
• AI systems are rapidly becoming more complex with multiple model chains
• Many current "agents" are just really, really long prompts (Mark's hot take)
• Task-specific models are emerging as one size won't fit all use cases
• Evolution moves from human-driven AI to agent-assisted to fully autonomous agents
• Agent readiness requires APIs that allow software to interact autonomously
• Traditional UIs become unnecessary when agents interface directly with systems
• Core competencies shift when AI handles the actual "doing" of tasks
• Sales and marketing must adapt to agents delivering outcomes autonomously
• Go-to-market strategies need complete rethinking for an agentic world
• The agentic age is upon us and AWS partners should shape the future

Participants:

• Mark Relph – Director – Data & AI Partner Go-To-Market, Amazon Web Services

See 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 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 transformation
• Andy Jassy declares AI agents will fundamentally change how we work
• Three key trends make AI agents practical: smarter models, longer tasks, cheaper costs
• AI now beats humans on complex benchmarks for the first time ever
• Claude 3.7 cracked graduate-level reasoning where humans previously dominated completely
• AI evolved from brief interactions to managing sustained multi-step complex workflows
• Processing costs plummeted 99.7% making enterprise-grade AI economically viable at scale
• We're transitioning from 2023's adaptation era to 2025's human-AI collaboration era
• By 2028, AI will suggest actions to humans rather than vice versa
• Agents are autonomous software that plan, act, and reason independently with minimal intervention
• Agent workflow: receive human request, create plan, execute actions, review, adjust, deliver
• Four agent components: brain (LLM), memory (context), actions (tools), persona (role definition)
• AWS offers three building approaches: ready-made solutions, managed platform, DIY development
• Key enterprise applications: software development acceleration, customer care automation, knowledge work optimization
• Manual processes like accounts payable offer huge transformation opportunities through intelligent automation
• Deep process analysis is critical before deploying agents for maximum effectiveness
• Celonis pioneered process mining to help enterprises understand their actual workflow realities
• Companies are collections of interacting processes that agents need proper context to navigate
• Process intelligence provides agents with placement guidance, data feeds, monitoring, and workflow direction
• Celonis-AWS partnership demonstrates order management agents that automatically handle at-risk situations

Participants:

• Jeff Naughton – SVP and Fellow, Celonis
• Cristen Hughes – Solutions Architecture Leader, ISV, North America, Amazon Web Services

Further Links:

• Celonis Website
• Celonis on 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/

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 operations
• Built on "channel-less architecture" unlike traditional contact centers that added channels sequentially
• One interaction can move seamlessly between channels (voice, chat, SMS, social)
• AI applies across all channels simultaneously rather than per individual channel
• 700 customers, primarily banks and credit unions, 370 employees, headquartered in New York
• Targets 3,500 banks and credit unions across the United States market
• Focuses exclusively on financial services and other regulated industries
• AI for regulated industries requires different approach than non-regulated businesses
• Traditional contact centers had trade-off between cost and quality of service
• AI enables higher quality while simultaneously decreasing costs for contact centers
• Number one reason people call banks: "What's my balance?" (20% of calls)
• Financial services require 100% accuracy, not 99.999% due to trust requirements
• Uses AWS exclusively for security, reliability, and future-oriented technology access
• Real-time system requires triple-hot redundancy; seconds matter for live calls
• Works with Bedrock team; customers certify Bedrock rather than individual features
• Showed examples of competitors' AI giving illegal million-dollar loans at 0%
• "Responsible AI" separates probabilistic understanding from deterministic responses to customers
• Uses three model types: client models, network models, and protective models
• Traditional NLP had 50% accuracy; their LLM approach achieves 100% understanding
• Policy is "use Nova unless" they can't, primarily for speed benefits

Participants:

• Justin DiPietro – Co-Founder & Chief Strategy Officer, Glia

Further Links:

• Glia Website
• Glia 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/