Eval costs are the arithmetic of judging an agent's traffic. Grading methods differ in per-event cost by orders of magnitude, and at scale those differences dominate the bill. A deterministic check costs effectively nothing per event. Grading with a language model pays for inference on every event, and that price varies widely with the model chosen.
The gap comes from where costs land. Some methods carry their cost per event: every trace a model judges incurs an inference charge that recurs with traffic. Others carry their cost up front: a trained classifier's cost is paid once at training time, so grading an additional trace with it costs close to nothing. Because the per-event methods carry nearly all the marginal cost, total spend tracks the share of traffic that reaches them multiplied by traffic volume.
This arithmetic decides what evaluation is feasible. Low-probability failures surface only when a large share of traffic gets examined, so the per-event cost of grading caps how much traffic can be examined, and with it which failures can be observed at all.
7 questions
Answered, plainly.
Two ways to run Tessary.
Tessary is an open-source agent reliability platform. Cloud and self-hosted run the same workflow on the OpenTelemetry traces your agent already emits.
Tessary Cloud
We host it for you. Send your first trace with nothing to deploy and no model key.
- traces
- 10,000 per calendar month
- stored trace data
- 1 GB
- retention
- 30 days
- model credit
- $10, one-time, for triage and root-cause analysis
- credit card
- not required
Self-hosted Tessary
Run the open-source code on your own infrastructure with one command. Add your own model key for triage and root-cause analysis.
Self-host Tessary for me by following https://github.com/tessaryai/tessary/blob/main/setup.md
docker compose -f oci://docker.io/tessaryai/tessary:compose up -d -y