Compare

DarkMatter vs. the alternatives.

DarkMatter is not a replacement for LangSmith, MLflow, or Datadog. It is the independent audit layer that complements all of them.

Feature comparison

Capability	DarkMatter	LangSmith	MLflow	Datadog	Your own logs
Stored outside your system	✓ Yes	✗ No	✗ No	✗ No	✗ No
Tamper-evident hash chain	✓ Yes	✗ No	✗ No	✗ No	✗ No
Customer signing keys (L3)	✓ Yes	✗ No	✗ No	✗ No	✗ No
Offline verifier (open-source)	✓ Yes	✗ No	✗ No	✗ No	✗ No
OpenTimestamps anchor	✓ Yes	✗ No	✗ No	✗ No	✗ No
Trace / step-level debugging	— No	✓ Yes	✓ Yes	✓ Yes	✗ No
Training data management	— No	✓ Yes	✓ Yes	✗ No	✗ No
Metrics / dashboards	— No	✓ Yes	✓ Yes	✓ Yes	✗ No
Framework-agnostic	✓ Yes	✓ Yes	✓ Yes	✓ Yes	✓ Yes

Use all of them

DarkMatter is the independent record. The others are operational tools.

Use LangSmith for debugging. Use MLflow for experiments. Use Datadog for infrastructure. Use DarkMatter when you need a record that survives a dispute, audit, or regulatory inquiry — one that neither you nor DarkMatter can alter after the fact.

Use LangSmith when

You need trace-level debugging

Step-by-step execution visibility, prompt management, and evaluation. The best tool for iterating on agent behavior.

Use MLflow when

You’re managing experiments and models

Training runs, model registry, evaluation pipelines. The standard for ML lifecycle management.

Use Datadog when

You need infrastructure observability

Latency, errors, resource usage, alerts. The right tool for production reliability.

Use DarkMatter when

The record has to survive a challenge

Audits, disputes, regulatory inquiries, counterparty verification. The independent layer that none of the others can be — because they all live inside your system.

Get started

Add the independent layer.

One import. Works alongside every other tool in your stack.

Start recording →Read the docs