Provenance and lineage for AI systems.
Attach identity to every embedding and verify it when it is used. Works with your existing system. Two calls to get started.
Use via API or run inside your infrastructure.
On insert, Mnemo attaches a signed identity to the embedding. On retrieval, your services confirm the embedding came from a known source and has not been altered. Works with your existing system.
Two integration points: embed() and verify(). Storage is optional. No vector database required.
Install the SDK. Wrap your embedding step with embed(). Wrap your retrieval step with verify(). Your model and your storage stay where they are.
from mnemo import Mnemo
mn = Mnemo()
# on insert
vec = model.embed(doc)
wm = mn.embed(vec, source="docs/policy.pdf")
store.upsert(wm.vector)
# on retrieve
for r in store.query(q, top_k=5):
if mn.verify(r.values).intact:
ctx.append(r)Mnemo focuses on one layer: attaching identity to embeddings and verifying them when they are used.
Create a workspace, register a service, issue a credential, and run your first verified embedding. The free tier covers small pipelines.