They tell you a score moved. Tessary tells you why.
Langfuse and Braintrust are good trace stores and eval runners, and Tessary connects to both. The difference is what happens after a score drops: they hand you the traces, Tessary hands you the change that caused the drop.
Score tracking and cause finding are different jobs
This is not a weakness of those tools; it is a different job. An eval platform tells you how the agent is scoring. A reliability platform tells you what to fix when the score drops.
Langfuse / Braintrust
Track scores, store traces
- Capture traces and spans from your agent
- Run the evals and LLM-as-judge scoring you configure
- Chart scores over time and per deploy
- When a score drops, the investigation is yours: open traces, read spans, guess at the cause
Tessary
Detect the drop, name the cause
- Reads grader trends over real traffic, robust to imperfect graders
- Traces a failing dimension back through the agent’s chain
- Names the change: prompt edit, tool update, dependency bump, upstream shift, provider update
- Covers causes that never appear in any diff
Where each tool starts and stops
Both columns are honest. Langfuse and Braintrust are strong at what they do; the row that matters is the one only Tessary answers.
| Tessary | Langfuse / Braintrust | |
|---|---|---|
| Traces and spans | Agent-native model, or pulled from your existing stack | Yes, core strength |
| Run evals and LLM-as-judge scoring | Yes, drafted from observed behavior and corrected by you | Yes, you author and maintain the setup |
| Score dashboards over time | Yes, read as trends robust to noisy graders | Yes |
| Tell you which change moved a score | Yes, this is the product | No, investigation is manual |
| Cover causes outside the diff (provider updates, upstream shifts, tool drift) | Yes, attribution walks the chain, not just the commit log | No |
| Pre-deploy risk read on a PR | Yes, the same attribution engine pointed at the next change | CI eval runs you configure |
| Works with the other tool | Pulls from Langfuse and Braintrust on demand | Tessary connects as a consumer |
Keep your stack, add the answer
The shipped integration is a pull connector, so adding Tessary is additive: your instrumentation, dashboards, and eval runs stay where they are.
Keep your trace stack
Langfuse and Braintrust are shipped Tessary connectors. Connect one as an upstream source and pull a chosen slice of traces on demand. Nothing gets re-instrumented and nothing moves.
Graders run on the pulled traffic
Tessary drafts graders from your agent’s observed behavior and stated intent; you correct them rather than write them from scratch. Each grader watches one quality dimension over real traffic.
The trend flags a real change
Verdicts are read as a trend over time, not one by one. An imperfect grader misfires at a stable rate, so a jump from 3% to 11% signals a real regression even when individual verdicts are noisy.
Attribution names the change
When a grader trend drops, Tessary traces the failing dimension back through the agent’s chain to the change that caused it: a prompt edit, a tool update, a dependency bump, an upstream agent’s shift, or a provider model update that never touched your repo.
Questions about the comparison
Related pages
Find out what moved the score.
Connect your Langfuse or Braintrust source and run the first grader trends on traffic you already have. When one drops, Tessary names the change behind it. No credit card required.