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Product coverage

Traces

Datasets

Evals

Optimise

Train

Serve

Overmind

covered:OTLP + Langfuse
covered:full
covered:full
covered:full
covered:full
covered:full

Langfuse

covered:OTel + 100 integrations
covered:versioned
covered:judge + code
partial:manual playground
not offered:export only
not offered:BYO model key
coveredpartialnot offered

Langfuse describes fine-tuning as an export: trace data leaves for external tools. Overmind is one of the places it can go, connector included.

Which one fits you

Decision tree

Question 1 of 3, Is your agent in production, logging real runs?

Is your agent in production, logging real runs?

Three of the seven verdicts here end at Langfuse. An MIT licence and regional data residency are two things Overmind has no answer to.

Product comparison

Overmind and Langfuse compared, 24 August 2026
OvermindLangfuse
LicenceCommercial. Trained weights are yoursMIT, entire product, no usage limits
Self-hostingPlatform is cloud. Trained weights run anywhereWhole platform, free forever. Helm and Terraform
Fine-tuningLoRA or full, hyperparameters recommended from your dataNone. Data exports for external tools
Model servingOpenAI-compatible endpoint, weights downloadableNone. Playground and judges use your API keys
Prompt improvementOptimiser ships scored diffs as PRsVersioned prompts, instant rollbacks, manual editing
Proof before switchingBenchmark vs production model, overlap-checkedExperiments on datasets, app-level
Data residencyCloud. SOC2 and HIPAA-ready pathways on EnterpriseIsolated EU, US, Japan, and HIPAA regions
PricingFree / Pro + credits. Ingest never credit-gatedFree 50k units/mo; $29, $199, $2,499 tiers; self-host $0

Common questions

Is Overmind a replacement for Langfuse?

It does not have to be. The common pattern is Langfuse for observability, Overmind for the loop from its traces to datasets, evals, and a trained model, via the live import connector. Overmind ships its own tracing too, so starting fresh with one tool also works.

Does Langfuse do fine-tuning or serving?

No. As of August 2026 its docs describe exporting trace data for fine-tuning in external tools, and every model-touching feature uses your own provider API key. It observes and evaluates models; it does not train or host them.

Langfuse self-hosts for free. What does Overmind cost?

Free and Pro subscriptions plus credits for compute-heavy work: dataset analysis, evals, optimisation, training, serving. Trace ingest never draws credits. If the requirement is a free self-hosted trace store, Langfuse wins that outright; Overmind's pitch is the loop, not the store.

Can I migrate gradually?

Yes. Backfill via the connector while your instrumentation stays put, and curate datasets from imported traces. Add Overmind's OTel endpoint alongside Langfuse's later if you want live scoring. No rewrite at any step.