LLM observability (open source)
TVIJO vs Langfuse
Langfuse is best-in-class for open-source LLM tracing and evals. TVIJO is a control plane: it does lighter observability but adds the routing, spend and governance layers Langfuse intentionally leaves to other tools.
What Langfuse does well
Langfuse is a strong open-source observability platform: detailed traces, evals, prompt management, datasets and self-hostable analytics for LLM apps. If deep tracing and experimentation are your priority, Langfuse is excellent and developer-loved.
Where TVIJO fits
TVIJO focuses on operating and governing AI in production — routing across providers, capping spend, enforcing policy, and producing audit evidence. Its tracing is intentionally lighter than a dedicated observability tool's.
Capability comparison
| Capability | TVIJO | Langfuse |
|---|---|---|
| Deep tracing of LLM calls | Partial | ✓ |
| Evals & experiments | Partial | ✓ |
| Prompt management | Partial | ✓ |
| Self-hostable / open source | Partial | ✓ |
| Model routing across providers | ✓ | — |
| Budget guards / spend caps | ✓ | — |
| BYOK key vault | ✓ | — |
| Audit evidence export (auditor-ready) | ✓ | Partial |
| EU AI Act readiness workflows | ✓ | — |
Choose Langfuse if…
- You want the deepest possible tracing and evals.
- You prefer a self-hosted, open-source stack.
- Experimentation and prompt iteration are your main workflow.
Choose TVIJO if…
- You need routing and spend control, not just visibility.
- You need compliance evidence for reviews and auditors.
- You want one operating layer rather than observability plus separate tools.
In short: TVIJO is not a replacement for Langfuse-grade observability. Many teams run Langfuse for deep tracing and use a control plane like TVIJO for routing, spend and governance. The two are complementary.