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TOLVYN vs Langfuse

Two different jobs

Langfuse is an excellent open-source LLM engineering platform — tracing, evaluations, prompt management. It's built to help you debug and improve quality, and its SDK is async by design: it observes from the side and never blocks a request.

TOLVYN is the opposite by design. It sits inline, so it can attribute every call to a customer and enforce a budget — not just record what already happened. This isn't better versus worse; it's two different jobs.

Side by side

Capability TOLVYN Langfuse
Architecture Inline proxy Async observability, beside the path
Primary job Financial attribution + enforcement Tracing, evals, quality
Can stop runaway spend before it lands Yes — hard budgets block at the proxy No, observes only
Per-end-customer cost attribution Financial-grade Cost shown per trace
Immutable hash-chained ledger, verifiable on demand Yes No
Best for Billing and margin accuracy across clients Debugging and improving LLM apps

Because Langfuse is async, it can't enforce — by the time a trace is flushed, the spend already happened. TOLVYN's hard budgets block the request at the proxy, before the provider is ever called. That's the core difference: Langfuse tells you what happened; TOLVYN can stop what shouldn't.

The ledger is the difference

Observability tools tell you what happened. TOLVYN gives you a record you can prove wasn't altered. Every metered request writes one ledger entry, and the entries are chained.

Each ledger record is hash-chained (SHA-256) and signed with HMAC-SHA256 using a per-tenant key. Sequence numbers are allocated under a Postgres advisory lock per tenant — no gaps, no duplicates, even under concurrent writes. Anyone can re-derive the chain and pinpoint the first tampered record with tolvyn ledger verify. The ledger entry is written in the same transaction as the request it accounts for, so there are no orphaned or partial records.

That's what turns "our dashboard says we spent $X" into evidence a finance team or auditor can actually rely on. No mainstream observability tool ships a tamper-evident cost ledger — it's a different design goal.

Which should you choose?

Choose Langfuse if…

  • You're debugging why an LLM response happened and whether it was good.
  • You need evals, prompt versioning, and tracing across chains and agents.
  • Your priority is application quality, not financial enforcement.

Choose TOLVYN if…

  • You need to attribute every dollar to a team, service, user, or customer.
  • You need budgets and quotas that block runaway spend before it happens.
  • You need a tamper-evident audit trail finance or compliance can rely on.
  • You want metadata-only governance — no prompt or response content stored.

Many teams run both: Langfuse for quality, TOLVYN for the money. They don't overlap.

Moving from Langfuse

Moving to TOLVYN takes minutes — change one import or point your client at the proxy. See the migration guides.

Read the migration guide →   Start free