Langfuse is an open-source LLM observability tool with strong developer features: prompt management, playground, evals, datasets. monsys.ai tackles a different slice: passive audit-grade observability with PII redaction at the source and signed evidence packs for the AI Act and NIS2. They both have a place.
| Dimension | monsys.ai | Langfuse |
|---|---|---|
| Primary use case | ✓Audit, compliance, governance — proof the system behaved | ✓Developer feedback loop — debug, eval, iterate prompts |
| PII redaction at source | ✓Built in and mandatory: IBAN-BE, RRN, BTW, KBO, email, phone — checksum-validated | ~Possible via SDK pre-processing or self-hosted plugin |
| Evidence pack export (Ed25519-signed) | ✓One click: tarball + manifest + offline verifier — for AI Act art.12 / NIS2 | ✗Not available — exports are CSV/JSON, unsigned |
| Prompt management & playground | ✗Intentionally none — monsys is passive, not an iteration/test tool | ✓Versioned prompts, playground, A/B comparison |
| Evals & datasets | ✗Not available — out of scope | ✓Built-in eval runners, datasets, LLM-as-judge |
| Cost & token tracking | ✓Versioned per-model pricing — OpenAI/Anthropic/Google/Mistral/Azure | ✓Per-trace and per-user cost tables |
| Hosting | ~Managed only — EU only, Belgium (GoTrust BV). No self-host, to keep the audit chain controlled. | ✓Managed (EU + US regions) or self-host |
| Wire format | ~Custom JSON envelope — small SDK (Python/Node/Go ~150 LOC) | ✓OpenTelemetry GenAI compatible + own SDKs |
| Anomaly alerts (cost/refusal/PII spikes) | ✓Built in: 7-day z-score baseline, ntfy push + hash-only webhook | ~Via custom evals or external alerting integrations |
| Open-source license | ✗Source-available, not open source — commercial hosted | ✓MIT (core) + Cloud subscription for managed |
Langfuse is a mature LLM observability platform with a ~3-year head start and a lively open-source community. monsys.ai's AI layer is new (2026) and deliberately narrower — no prompt management or evals, but audit-grade evidence and EU/BE-specific PII detection. For many teams the right answer is: Langfuse for dev iteration + monsys for compliance evidence.