Rootline reads your Langfuse traces, explains each failed run, groups failures into issues, turns them into regression tests, and shows what every customer and feature costs.
Illustrative preview with sample numbers, not real customer data.
No SDK changes and no data migration. Keep using Langfuse.
Paste your project host and API keys. Rootline pulls traces and observations through the Langfuse public API.
Each failed or suspicious run gets a plain-English reason and a concrete suggested fix, with the failing step highlighted.
Failures with the same root cause become one issue, ranked by severity, and each issue becomes a regression test.
Built for small teams and AI agencies running agents in production.
Why the run failed and what to change, not just another trace view.
Errors, loops, empty or malformed tool output, ignored tool results, timeouts and cost spikes, grouped by cause.
See every tool call and model step, with the failing step marked.
Export failures as JSON or a pytest file and run them before each release.
Spend per customer, feature and run, with alerts for runaway loops.
A Monday summary of top issues and spend your team, or your agency clients, can read.
Priced by failed runs analyzed per month. Healthy runs are never billed.
Exact run limits will be published before launch.
No. Rootline reads the traces you already send to Langfuse, including self-hosted Langfuse.
Langfuse today. OpenTelemetry and LangSmith are planned.
Today, explanations and suggested fixes are rule-based: built-in rules find the failing step and explain the cause in plain English. AI-written explanations are planned.
Errors, timeouts, loops, empty or malformed tool output, tool results the agent ignored, and unusually expensive runs.
Each workspace's data is isolated. Rootline only needs read access to traces and observations.