Own the ground truth
your AI runs on.
AgentModus learns what 'good' means for your tasks - from your own traffic. With that ground truth, you can route models with confidence, know if a prompt change helped, catch regressions before users do, and bring down cost.
Your evals are your most valuable AI asset.
The models are rented - everyone runs the same ones. What you own is the ground truth on top: a private benchmark, built from your own production traffic, that measures whether your AI is improving on your real work. That compounds as your IP. AgentModus builds it.
How AgentModus works
The problem
You’re flying blind.
You can’t tell if a cheaper model is safe to run, or where your agent is quietly failing. Without a bar of your own, every model choice is a guess.
Quality: unknown
The solution
Learn the bar from your own traffic.
AgentModus learns what “good” means for each of your tasks - straight from your production data. That bar is your ground truth: a private benchmark you own.
Route with confidence
Run the right model for every task.
Once the bar is set, every task can drop to the cheapest model that still clears it - and you have the proof it holds. Spend falls, quality stays.
Catch regressions
See exactly where and why you fail.
Every miss is surfaced with the task and the reason - so quality regressions never reach your users quietly again.
Flagged before it reached users
Improve with proof
Turn every change into measured improvement.
Ship a prompt, model, or agent change and see - against your own bar - whether it actually moved quality up. Your AI gets better because you can finally measure what ‘better’ means.
Measured against your 0.84 bar
One layer. The whole surface area.
Everything your learned bar unlocks, at a glance.
Cut your model spend
Run the cheapest model that clears your bar - then swap freely and spend less. Without losing quality.
Catch silent regressions
When a model update, prompt change, or drift quietly lowers your output quality, the bar flags it - before your users do.
Validate every change
Know if a new prompt, model, or agent tweak actually helped.
Prove your quality
Show customers and your team a measured bar, not a vibe.
Frequently Asked Questions
It's the private evaluation layer of your learning loop. It learns what 'good' means for each of your AI tasks - straight from your own production traffic - and turns that into a private benchmark you own. With that bar in place, it routes each task to the cheapest model that still clears it, and flags regressions before they reach your users.
From your real production traffic. AgentModus learns the bar per task from how your AI actually performs and the outputs you accept, so you are not hand-writing eval sets from scratch. The result is a benchmark you own.
No. AgentModus is a drop-in endpoint that sits in front of the models you already run. Point your agents at it, keep your own provider keys, and it starts capturing traffic in minutes.
No - we sit on top. Keep LiteLLM, your gateway, whatever you run. We're the intelligence layer that tells it what's safe, via a drop-in endpoint or a lightweight SDK.
It is model-agnostic - the major providers and open models. Once the bar is set for a task, AgentModus compares models against it and picks the cheapest one that still clears it, re-checking as new models ship.
That is what the bar is for. A cheaper model is only used for a task once it has been measured to clear your benchmark - so the goal is lower spend with quality held, and the measurement to back it up. If a model can't clear the bar, it isn't used.
It evaluates your outputs against the bar learned for each task - combining automated scoring with your own signals, like the outputs you accept, edit, or revert. The aim is a benchmark that reflects your real standard, not a generic one.
Yes - that's a core use. Because we measure against your learned bar, you can see whether any change (prompt, model, agent logic) actually helped or quietly hurt.
Your traffic and your benchmark stay yours. Your ground truth is not shared with or exposed to anyone else. We're happy to put the specifics in a data agreement before any traffic flows.
Pricing scales with your usage and the models you run. Book a call and we'll size a plan to your traffic.