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Ep142: Transforming ISV Businesses Through Modern Data Platforms with Coveo, DTEX Systems and Honeycomb
Episode 142

Ep142: Transforming ISV Businesses Through Modern Data Platforms with Coveo, DTEX Systems and Honeycomb

AWS for Software Companies Podcast · Nate Goyer

September 8, 202544m 12s

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Show Notes

Three leading ISV executives from Coveo, DTEX Systems and Honeycomb, reveal how companies with proprietary datasets are gaining unbeatable competitive advantages in the AI era and share real-world strategies how you have similar outcomes.

Topics Include:

  • Panel introduces three ISV leaders discussing data platform transformation for AI
  • DTEX focuses on insider threats, Coveo on enterprise search, Honeycomb on observability
  • Companies with proprietary datasets gain strongest competitive advantage in AI transformation
  • Data gravity concept: LLMs learning from unique datasets create defensible business positions
  • Coveo maintains unified enterprise index with real-time content and access rights sync
  • Honeycomb enables subsecond queries for analyzing logs, traces, and metrics at scale
  • Multi-tenant architectures balance shared infrastructure benefits with single-tenant data separation
  • Coveo deployed 140,000 times last year using mostly multi-tenant, some single-tenant components
  • DTEX scaled from thousands to hundreds of thousands endpoints after architectural transformation
  • Capital One partnership taught DTEX how to break monolithic architecture into services
  • Apache Iceberg and open table formats enable interoperability without data duplication
  • Honeycomb built custom format following similar patterns with hot/cold storage tiers
  • Business data catalogs become critical for AI agents understanding dataset context
  • MCP servers allow AI systems to leverage structured cybersecurity datasets effectively
  • DTEX used Cursor with their data to identify North Korean threat actors
  • Real-time AI data needs balanced with costs using right models for jobs
  • Caching strategies and precise context reduce expensive LLM inference calls unnecessarily
  • Search remains essential for enterprise AI to prevent hallucination and access information
  • ROI measurement focuses on cost reduction, analyst efficiency, and measurable business outcomes
  • Key takeaway: invest in data structure early, context is king, AI is just software


Participants:


Further Links:


See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/


 

Topics

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