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What “AI-Ready Data” actually means for observability teams

Blog post from Coralogix

Post Details
Company
Date Published
Author
Micha Duman
Word Count
1,707
Company Posts That Month
14
Language
English
Hacker News Points
-
Post removed?
No
Summary

Many organizations deploying AI face challenges not with AI models themselves, but with the underlying data, as approximately 60% of AI projects are abandoned due to a lack of AI-ready data, according to Gartner. This issue extends to observability data, which is highly valuable but traditionally structured for human use, not for AI consumption. Coralogix aims to transform observability by developing an AI-ready data layer that allows AI agents to interact with telemetry data conversationally, enhancing operational intelligence across various organizational roles. This involves a shift from traditional query-based interactions to dynamic, context-aware conversations facilitated by their DataPrime query language and living schema architecture. The approach enables comprehensive data access without the need for costly indexing, ensuring that AI agents can efficiently analyze and correlate data across different domains. By organizing data into governed domains, Coralogix provides a robust framework for AI-driven workflows, leading to improved pattern recognition and operational excellence, positioning their platform as a key enabler of next-generation AI capabilities.

Trends Found in this Post
Trend Post Mentions Total Month Mentions Posts Companies MoM
Observability 19 4,496 812 176 +40%
AI Agents 11 4,430 1,100 236 -3%
AI Coding Assistant 2 1,480 382 153 +18%
Multi-agent systems 1 460 170 68 -20%
Real-time 1 6,296 1,346 246 -2%
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