Every session becomes intelligence.
IronBee analyzes every agent session and turns it into signal you can trust: the time, cost, and quality of each run, the findings that matter, and recommendations where they help.
Every token, accounted for.
CostBilled spend and shadow spend, side by side: what you actually paid the API, and what your subscription absorbed. Broken down by model, plan, project, team, user, and session.
Every session, measured.
InsightsCost, turns, context pressure, rhythm, the real shape of how a session ran. IronBee captures it live, as it happens, so what you see is what actually occurred, not a guess.
Is it actually getting better?
QualityThe trends that answer it: pass rate, re-fail rate, and rework, week over week, revealing whether fixes hold, how rigorously the agent verifies, and where failures keep coming back.
Findings that explain, recommendations that resolve
Findings & RecommendationsEvery analysis ends in findings, scored by severity, scoped to a project or the whole account, and backed by evidence, so you know exactly what happened and why. The ones that matter carry a recommendation: a concrete action you can trace straight back to the finding behind it. Click a finding to read one.
Two projects and one heavy user drive most of the spend, with no owner watching the concentration
Across the 8 projects, ml-pipeline ($2636) and admin-portal ($1560) carry 78% of the $5380 combined cost, but most of the billed spend comes down to one person: David alone drives 69% of it, more than double Michael and Sarah combined. Nobody owns that number, so the single biggest cost lever has no one accountable for pulling it.
Evidence:Ready to ship
AI-generated code with confidence?
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