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

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.