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CEO Joe Kim shares how Sumo Logic has implemented generative AI to democratize data analytics, leveraging AWS Bedrock's multi-agent capabilities to dramatically improve accuracy.
Topics Include:
- Introduction of Joe Kim, CEO of Sumo Logic.
- Question: Overview of Sumo Logic's products and customers?
- Sumo Logic specializes in observability and security markets.
- Company leverages industry-leading log management and analytics capabilities.
- Question: How has generative AI entered this space?
- Kim's background is in product, strategy and engineering.
- Non-experts struggle to extract value from complex telemetry data.
- Generative AI provides easier interface for interacting with data.
- Question: How do you measure success of AI initiatives?
- Focus on customer problems, not retrofitting AI everywhere.
- Launched "Mo, the co-pilot" at AWS re:Invent.
- Mo enables natural language queries of complex data.
- Mo suggests visualizations and follow-up questions during incidents.
- Question: What challenges did you face implementing AI?
- Team knew competitors would eventually implement similar capabilities.
- Single model approach topped out at 80% accuracy.
- Multi-agent approach with AWS Bedrock achieved mid-90% accuracy.
- Bedrock offered security benefits and multiple model capabilities.
- Question: How was working with the AWS team?
- Partnered with Bedrock team and tribe.ai for implementation.
- Partners helped avoid pitfalls from thousands of prior projects.
- Question: What advice for other software leaders?
- Don't implement AI just to satisfy board pressure.
- Identify problems without mentioning generative AI first.
- Innovation should come from listening to customers.
- Question: Future plans with AWS partnership?
- Moving toward automated remediation beyond just analysis.
- Question: Has Sumo Logic monetized generative AI?
- Changed pricing from data ingestion to data usage.
- New model encourages more data sharing without cost barriers.
Participants:
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