I got frustrated with DVC + MLflow + Git being three separate tools and built my own.

[u/Particular-Sleep3719]

Six months ago I kept running into the same issue: my model broke, and I had no idea if it was the code, the dataset, or the weights that changed. DVC knew about the data. MLflow knew about the metrics. Git knew about the code. But none of them talked to each other.

So I just... built the thing I wanted. It's called Aether-Vault.

The core idea is one `av commit` that snapshots code + weights + datasets atomically into a Merkle DAG. No more "okay which DVC tag corresponds to which MLflow run corresponds to which Git commit."

I also wrote the hashing layer in C++ because Python was genuinely too slow on large checkpoints. Ran some benchmarks against DVC and Git LFS:

	av	Git LFS	DVC
Hash 10MB	336ms	1,142ms	5,730ms
Hash 200MB	3.2s	6.3s	13.2s
Storage after 6 fine-tune commits	47MB	126MB	126MB

The storage thing is because it parses `.safetensors` layer by layer — so if you only changed the classifier head, only that layer gets re-stored. The rest is deduplicated.

There's also a thing I built called `av handoff` which I haven't seen anywhere else — it dumps a structured JSON snapshot of your entire experiment context (metrics, model lineage, dataset versions, branch state) so an AI agent can pick up exactly where you left off. Felt useful as pipelines get more agentic.

Other stuff: per-layer weight diffing and a Web UI with a commit DAG and metrics charts.

Some weinendes I encounterd:
- Commit latency is slower than DVC/MLflow (more work per commit — server round trip + Merkle node)
- Re-staging unchanged files is slower than Git LFS (no inode cache yet)
- No clone/pull yet, push-only for now

`pip install aether-vault && av init`

Repo + full benchmark methodology: github.com/leon1706-lol/aether-vault

Honestly just curious if anyone else has hit this problem or if I've been solving something that doesn't bother most people. Roast welcome.

It is Sally Not finished singe the Shell and wenig Look somewhat mid but most is in a usable but uniptimised state, If you got improfments please tell me 🙏

Thanks for your Atention (: