Says 60 days. The retrieved policy says 30.
Refunds are available within 30 days of delivery.
Both take your OpenTelemetry traces. Confident AI scores every one of them, builds your datasets from production, catches drift and simulates conversations. Switch in three steps and keep your spans.
You shouldn't need to export traces just to annotate them. Customize review forms, annotate traces, and turn feedback into test cases.
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“Before Confident AI, a single improvement cycle took 10 days — I'd create a task, assign it to an engineer, wait for availability, and go back and forth. Now the same cycle takes three hours, and our product managers can run it themselves.”
Automatically flag failures, explain what went wrong, and route traces to the right SMEs for annotation.
Metrics auto-evaluated on every ingested trace.
“Confident AI saves us 480+ hours of manual AI evaluation every month — and gives us the data to defend every quality decision in front of engineering, product, and leadership.”
Simulate users, test follow-ups, and evaluate full conversations before your agents reach production.
2,400 conversations
“We run a lot of large-scale, multi-turn simulations, and Confident AI made it far easier to design scenarios and execute those tests without piecing together external tools.”
See what changes for your team. Compare workflows for PMs, engineers, QAs, and SMEs.
| Feature | Confident AI | Langfuse |
|---|---|---|
Validate evals Check automated scores against human judgment | ||
Surface issues automatically Find recurring failures from production feedback | ||
Find product insights Understand patterns in real conversations | Not assessed | |
Find struggling users See which users experience failures and poor responses | Not assessed | |
Cross-functional workflows PMs and QA run evals without engineering |
Before Confident AI, a single improvement cycle took 10 days — I'd create a task, assign it to an engineer, wait for availability, and go back and forth. Now the same cycle takes three hours, and our product managers can run it themselves.
Confident AI saves us 480+ hours of manual AI evaluation every month — and gives us the data to defend every quality decision in front of engineering, product, and leadership.
Confident AI gave our team one place to turn production failures into datasets, align metrics, and keep regressions out of releases without waiting on custom engineering work.
We run a lot of large-scale, multi-turn simulations, and Confident AI made it far easier to design scenarios and execute those tests without piecing together external tools.
Thanks to Confident AI, we were able to move to a fine-tuned model and cut our LLM costs by 80%. This opens up whole new use cases now to generate better output with more targeted LLM calls.