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

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