Ryan Steeb shares DTEX Systems’ strategic approach to implementing generative AI with AWS Bedrock, reducing risk while focusing on meaningful customer outcomes.
Topics Include:
- Introduction of Ryan Steeb, Head of Product at DTEX Systems
- Explanation of insider risk challenges
- Three categories of insider risk (malicious, negligent, compromised)
- How DTEX Systems is using generative AI
- Collection of proprietary data to map human behavior on networks
- Three key areas leveraging Gen AI: customer value, services acceleration, operations
- How partnership with AWS has impacted DTEX's AI capabilities
- Value of AWS expertise for discovering AI possibilities
- AWS Bedrock providing flexibility in AI implementation
- Collaboration on unique applications beyond conventional chat assistants
- AWS OpenSearch as a foundational component
- Creating invisible AI workflows that simplify user experiences
- The path to monetization for generative AI
- Three approaches: direct pricing, service efficiency, operational improvements
- Second and third-order effects (retention, NPS, reduced churn)
- How DTEX prioritizes Gen AI projects
- Starting with customer problems vs. finding problems for AI solutions
- Business impact prioritization framework
- Technical capability considerations
- Benefits of moving AI solutions to AWS Bedrock
- Fostering a culture of experimentation and innovation
- Adopting Amazon's "working backwards" philosophy
- Balancing customer-driven evolution with original innovation
- Time machine advice: start experimenting with Gen AI earlier
- Importance of leveraging peer groups and experts
- Future outlook: concerns about innovation outpacing risk mitigation
- Security implications of Gen AI adoption
- Participation in the OpenSearch Linux Foundation initiative
- Final thoughts on the DTEX-AWS partnership
Participants:
- Ryan Steeb – Head of Product, DTEX Systems
See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/
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