the loop
The loop, closed.
Most tools show you what your AI did. Looptail runs the whole loop: it watches every decision, judges it against your standards, and ships the fix — with a signed record of each pass.
01
Observe
An SDK and proxy capture every decision: inputs, retrieved context, tool calls, output, and the downstream outcome signals that tell you whether it worked.
02
Understand
Continuous evaluators — rubric agents encoding your own standards, not generic metrics — score live traffic, detect drift, and cluster failures into tracked issues.
03
Improve
Looptail proposes patches — prompt, policy, routing, few-shot — replays them against curated regression sets, canaries them, and promotes them through the approval gates you choose.
Your standards, not generic metrics
Off-the-shelf metrics tell you a response was fluent. They don't tell you it violated your refund policy. Looptail evaluators are rubric agents you write against your own policies and product bar, versioned like code, and run on live traffic — so your test set never rots while your system changes.
Fixes ship through gates, not hope
Every proposed change replays against regression sets built from your real failures, then canaries on a slice of traffic. You decide which changes need a human sign-off and which can promote automatically. Either way, the change lands with the evidence that motivated it attached.
Evidence is a by-product, not extra work
Because the loop runs through Looptail, the record writes itself: observation, judgment, patch, approval, outcome — signed, append-only, exportable. That record is the Tail.