Gartner® Report:
Coralogix Named a Market Shaper in the October 2026 Gartner® Emerging Market Quadrant for AI FinOps Tools — Startup Vendors
Gartner has recognized Coralogix as a Market Shaper in the Gartner® Emerging Market Quadrant for AI FinOps Tools — Startup Vendors. We’re proud to share this recognition and what we believe it means for teams running AI in production.
A Market Shaper in AI FinOps
AI is changing the economics of running software. As teams move agents, coding assistants and multi-model applications into production, token spend gets harder to predict, attribute and control.
In our view, this recognition reflects the approach Coralogix has taken from the start: connecting AI observability with the financial controls teams need to scale AI with confidence. You can’t manage AI spend without seeing the systems and workflows driving it.
Gartner notes that “this emerging market is increasingly shifting beyond cost reporting toward AI economics management.”1
What We Believe Makes Us a Market Shaper
Visibility and control over AI consumption across coding assistants, production applications and autonomous agent workflows, on one observability platform.
Coding-agent cost intelligence
Code AgentOps tracks spend, tokens and usage across Claude Code, Cursor, GitHub Copilot, Codex CLI and Gemini CLI, attributed by user, team, repository and model. Coralogix monitors ~19,500 coding-agent users today, and a global professional services firm uses it to attribute GitHub Copilot and LLM spend by user, model, session and repository.
Agent-level cost visibility
Connect token consumption and model activity to end-to-end execution traces. See cost per conversational turn or agent invocation, and find inefficient multi-agent handoffs.
Proactive budget controls
AI Units provide a normalized consumption model with organization-wide budget pools, per-user and per-group spending caps, forecasting and automatic circuit breakers.
- 1Gartner, Emerging Market Quadrant for AI FinOps Tools — Startup Vendors, Ray Collins, Adam Ronthal, Marco Meinardi, Nitish Tyagi, 28 October 2026.
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Observability that
was built for AI,
not repackaged for it
Run your agents and teams on the right foundation, so they don’t approximate, they know.