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
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