Use Case: Offline / Regulated Work
What you’re solving for
You work in a regulated industry (healthcare, finance, defense, legal), on an air-gapped machine, or under a policy that forbids sending source code to third-party services. You still want AI-assisted code understanding — without the code leaving the building.
Why NeuralMind fits
- No API calls. Indexing, embeddings, retrieval — all local.
- No cloud account required. No sign-up, no telemetry, no outbound network.
- No code uploaded anywhere. ChromaDB runs in-process.
- Pairs with local LLMs. Use with Ollama, llama.cpp, vLLM for an end-to-end local stack.
Fully local stack
pip install neuralmind
neuralmind build . # local embeddings, local vector store
Pair with a local model:
# Example: Ollama + NeuralMind
ollama pull llama3.1:70b
CONTEXT=$(neuralmind query . "how does auth work?")
echo "$CONTEXT" | ollama run llama3.1:70b "Explain the auth flow"
Nothing here touches the public internet.
Compliance-friendly properties
| Property | NeuralMind |
|---|---|
| Source code transmitted externally | Never |
| Telemetry | None |
| SaaS dependency | None |
| Account / login | None |
| Network required for install | Only to fetch the Python package — mirror it internally if needed |
| License | MIT (auditable) |
| Data at rest | graphify-out/ and .neuralmind/ inside your project |
| Data in transit | N/A (no outbound calls) |
Air-gapped install
- On a connected machine:
pip download neuralmind -d ./offline-bundle - Copy
./offline-bundle/to the air-gapped machine. - Install:
pip install --no-index --find-links ./offline-bundle neuralmind
ChromaDB pulls its embedding model on first use — download it in advance or point HF_HOME at a pre-populated directory.
Turning off query memory (if your policy forbids local logs)
export NEURALMIND_MEMORY=0
export NEURALMIND_LEARNING=0
Or decline the TTY consent prompt the first time neuralmind query runs. No events are logged.
Audit trail
Every action is a local file operation — easy to log via existing endpoint monitoring:
- Knowledge graph:
graphify-out/graph.json - Vector store:
graphify-out/neuralmind_db/ - Query events (only if opted in):
.neuralmind/memory/query_events.jsonl - Learned synapse memory:
.neuralmind/synapses.db(the Hebbian graph the synapse layer learns automatically from usage)
Delete any of these at any time — nothing persists outside your project.