ChainMail
ChainMail Council AI writes code faster than humans can review it.
Core trick
Parallel model votes gate AI code changes, followed by a hardware-key approval and a SHA-256 hash-chained audit log.
Description
ChainMail Council
AI writes code faster than humans can review it. There's no governance layer — no accountability, no audit trail, no way to know what changed, why, or who approved it.
Council is that layer.
Before any AI-generated change touches your codebase, a council of specialized models deliberates and votes. Codex — running inside JetBrains — reads the task, selects the right agents, and fires them in parallel against Nebius Token Factory: Qwen3 235B, Nemotron Ultra 253B, Nemotron 120B. Three independent MoE models. Three votes. A human verifies with a FIDO2 hardware key. Gemma on a sovereign VM synthesizes the consensus. Every deliberation writes to MMCP Bubble Memory — a pgvector store on our H100, semantically searchable, permanently retrievable. Every audit entry is SHA-256 hash-chained to the one before it. You can't delete a decision without breaking the chain.
Eight pillars: shared context · sovereign memory · BYOK · identity · accountability · retrievability · reversibility · ledgerbility
Stack: Nebius H100 VM · Nebius Token Factory (MoE) · NousResearch Hermes Agent · MMCP Bubble Memory · Supabase Edge Functions · OpenAI Codex (JetBrains) · FIDO2 Bkey · Snap Spectacles AR
This is the infrastructure layer that enterprise AI has been missing. Not a chatbot. Not a copilot. Governance.
missing the CMO = Gemma 4 + Apify + Mind AI + Vis-AI-Vis for customer discovery interviews. because knowing what and why is equally as important as knowing when and how. and IDEALLY for WHO!!!! apify pulls all social, mindsAI builds ICP, vis-ai-vis conducts the face to face with ai in the middle interviews. equals a governed result with the council. and creates the GTM!
Apify → pulls social signals (Reddit, X, LinkedIn, reviews)
Mind AI → builds ICP from those signals
Vis-AI-Vis → conducts AI-mediated face-to-face customer interviews
Gemma 4 → synthesizes into CMO brief (WHO + WHAT + WHY)
↓
CMO council vote — evidence-backed, not inferred
↓
Council consensus → governed GTM
README excerpt
# ChainMail Council
> Governance-gated AI code changes. Sovereign memory. Tamper-evident audit. Hardware-verified human in the loop.
AI writes code faster than humans can review it. There's no governance layer — no accountability, no audit trail, no way to know what changed, why, or who approved it. **Council is that layer.**
Before any AI-generated change touches your codebase, a council of specialized models deliberates and votes. Every decision is hash-chained and written to sovereign memory on a VM you control. You can't delete a decision without breaking the chain.
---
## Demo
```
python cli/demo.py --task "Add 429 rate limiting to the spectacles gateway"
```
```
[1] Bkey CMRAi — human verification gate
✓ Human verified
[2] Repo context scan
✓ Context ready
[3] Convening council...
Codex → picks agents · Token Factory → MoE deliberation
══════════════════════════════════════ ⚡ CHAINMAIL COUNCIL
task Add 429 rate limiting to the spectacles gateway...
agents cto, coo, cfo
memory ✓ MMCP Bubble Memory (VM)
time 36.6s
══════════════════════════════════════ DELIBERATIONS
⟳ CTO 95% Qwen/Qwen3-235B-A22B-Instruct-2507
Rate limiting is critical to prevent VM cost overrun...
→ Add token-bucket middleware before any business logic executes.
✓ COO 95% nvidia/Llama-3_1-Nemotron-Ultra-253B-v1
Session-based throttling ensures fair usage without degrading core functionality.
✓ CFO 92% nvidia/nemotron