Introducing Turn3 — the system of record for agent quality. First in a series on building trustworthy AI agents.
Picture the support transcript. Eight turns, agent and customer. Every single message is fluent, confident, well-formed. Every API call returned 200 OK. Your dashboards are green. Your error rate is zero.
And the customer left furious, because somewhere in that conversation the agent quietly got the facts wrong and then spent five turns building on the mistake.
Nothing threw an exception. Nothing looked broken. That’s the problem.
Agents don’t crash. They drift.
We spent years learning to monitor software that fails loudly. A service throws a 500. A latency graph spikes. A test goes red. You get paged, you find the stack trace, you fix the line.
AI agents don’t fail like that. They fail silently, and in slow motion.
The failure is rarely in a single response. It’s in the relationship between responses across a session. The agent misreads something the user established early — a constraint, a fact, an intent. That misreading doesn’t announce itself. The agent keeps going, confidently, building turn after turn on a foundation that’s subtly wrong. By the time something visibly breaks, you’re many turns downstream of the moment that actually caused it.
So when you go to debug it, you look at the turn that looks wrong — turn 8, say — and it makes no sense in isolation, because the cause isn’t there. The cause is back at turn 3, in a message that looked completely healthy at the time.
Root cause hides at turn 3. The visible symptom shows up at turn 8. Your logs, your evals, and your own eyes all skip right past the turn that mattered.
That gap has a name now. We called the company’s first product after it.
Why traditional tooling can’t see it
The instinct is to reach for the tools we already have — LLM observability, tracing, per-response evals. They’re useful, and Turn3 builds on the same open standards they do. But most of them share a blind spot: they evaluate responses one at a time.
Grading an agent response in isolation is like reviewing a conversation by reading every third word. You can confirm each word is spelled correctly and still have no idea whether the conversation went anywhere good. The failure modes that actually matter for agents — contradicting an earlier fact, losing the thread of the goal, dropping a constraint the user set three turns ago — are invisible to anything that only looks at one response at a time. It never saw the earlier turns.
To catch how an agent really fails, you have to evaluate the way a human reviewer would: read the whole session, understand what the user was trying to accomplish, and judge whether the agent actually accomplished it.
That’s the idea Turn3 is built on.
What Turn3 does
Turn3 is session-native. Instead of judging responses one by one, it reconstructs the entire session — every turn, tool call, and sub-agent — into a single, goal-oriented unit, and then works the way a good reviewer does:
- See the session. Turn3 rebuilds each agent run into a complete session from the telemetry you already emit — no proprietary SDK required.
- Judge the outcome. It scores whether the session’s actual goal was met, and attributes the failure to the exact turn where things went wrong — not the turn where the symptom finally surfaced.
- Cluster the failures. Individual failures group into tracked issues that know their own state: active, resolved, or regressed.
- Stop the regression. Turn3 turns real failures into evals automatically and gates your CI/CD, so a bug you’ve already fixed can’t quietly ship again.
That last point is the one teams underestimate. Model providers update silently. Prompts drift. A regression you fixed last month sneaks back in — and because it doesn’t throw an error, nothing catches it until a customer does. Turn3 makes fixed actually mean fixed, and keeps it that way.
Built to fit where your agents already live
A quality platform that requires you to rewrite your stack isn’t going to get used. So Turn3 meets your agents where they are.
It finds the breaking turn for agents built on frameworks like LangChain, LangGraph, and OpenAI Agents, and it pulls governed telemetry — with no exporter changes — from the platforms teams already run on, including Databricks, Snowflake, Azure Foundry, AWS SageMaker, and Gemini. Underneath, it speaks standard OpenTelemetry, OpenInference, and OpenLLMetry. No proprietary SDK. No lock-in. If you’re already emitting traces, first session is about twenty minutes away.
And because agent telemetry is some of the most sensitive data a company has, Turn3 runs in your cloud or fully self-hosted inside your own VPC, with prompts redacted at the edge — so sensitive data never has to leave your boundary.
Start by seeing your own turn 3
We built Turn3’s free tier around a simple belief: you should be able to see your own hidden failures before you pay us anything.
Free gives you full session reconstruction and failure-cluster previews — enough to watch your agents’ real failure patterns emerge from your own traffic. Point your exporter at Turn3, and the sessions start coming in.
The failures are already happening in your production agents right now. The only real question is whether you’ve seen them yet.
Where this goes
Launching Turn3 is the start of something bigger. As agents move from demos into the path of real customers and real money, “it seemed to work” stops being an acceptable standard. Teams need a place they can go to know — session by session, turn by turn — whether their agents are actually doing their job. That’s the category we’re building: the system of record for agent quality.
This post is the first in a series. In the ones that follow, we’ll go deeper on how session-native reconstruction actually works under the hood, how the closed loop turns failures into regression gates, and how Turnguard extends Turn3 from diagnosing yesterday’s failures to preventing today’s — inline, in the request path, before a bad response ever reaches a user.
If you’re putting agents into production, we’d love for you to build this with us.
Start free at klimber.io — or reach us at turn3@klimber.io.
Turn3 is a product of Klimber Technologies — the system of record for agent quality.