Stop your agents from failing silently.

Built for engineers running agents in production, Tessary watches every trace, catches what broke, and shows you why.

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

116

traces emitted in the last hour

3

sampled and evaluated

1

wrong, raised by a customer

how it works

Monitor every trace, not a sample.

Your agent already emits spans. Tessary reads all of them as they land – no sampling, no LLM call.

Filter down to what broke.

Twelve traces break the same way. Tessary groups them into one case.

Analyze them against your code.

We read the failing traces against your repo and find the change that explains it.

Know what to change.

You get the cause and the evidence behind it, minutes after the first bad trace.

case 1184 · checkout agent · 12 of 218 tracesreading repository…

tools/refund.py · changed in a1f9c2

11def resolve_refund(order, cust):
12payload = {"order": order.id}
13cust never reaches the payload
14return client.refund(payload)

all 12 failing traces hit line 13 · no healthy trace does

The refund payload lost customer_id.

12payload = {"order": order.id}
13payload["customer_id"] = cust.id
case
checkout agent · tool-call errors increased
change
0.4% → 11.2% in four hours
affected traces
218
likely cause
tool argument changed in commit a1f9c2
next step
restore customer_id in the refund payload

features

Self-host Tessary.

Free and open source. Point it at the traces your agent already emits.

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