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/