Two surfaces, one substrate
| Governs | how your AI writes code | what your deployed AI decides |
| Trigger | a code change | a production decision (loan, hiring, triage, …) |
| Emits | reviewed, impact-analysed, audit-logged changes | a tamper-evident, third-party-verifiable record per decision |
| Built on | typed code knowledge graph + multi-agent reasoning | Layer 5 cryptographic substrate (RFC 8785 JCS → RFC 6962 Merkle → ed25519 → Sigstore Rekor) |
| Status | GA | GA — attest() capture (v0.60.0) + FastAPI middleware / @governed (v0.61.0) + continuous anchoring worker graqle govern serve (v0.62.0) |
Build-time governance proves we hold ourselves to this standard — GraQle is developed through its own governance. Run-time governance lets you hold your deployed AI to the same cryptographically-verifiable standard. Same substrate, both surfaces.
90-second quickstart
Build-time — query your codebase as a graph
graq scan repo .
graq run "find every authentication bypass risk"
graq learn "cancel endpoint must require admin auth"
Run-time — attach governance to a deployed AI in one line
from graqle.governance.runtime import GovernedRuntime
gov = GovernedRuntime(salt="your-deploy-salt")
def score_application(app):
decision = model.predict(app)
gov.attest(
domain="loan", model_id="credit-risk-v4",
inputs={"applicant_ref": gov.pseudonymize_ref(app.id)},
output={"decision": decision.label, "reason_code": decision.reason},
)
return decision
Each call produces a durable, PII-safe governed record. Its leaf hash is computed with the same shipped primitive the build-time batcher uses, so a runtime record is byte-compatible with the cryptographic substrate (RFC 8785 JCS → RFC 6962 Merkle → ed25519 → Sigstore Rekor). Capture is out-of-band — it adds 0 ms to your write path.
See examples/runtime_attest_production_decisions.py and examples/runtime_govern_serve_anchoring.py.
Run it as a continuous service (v0.62.0)
graqle govern serve --config graqle.yaml
graqle govern serve --once
graqle govern health
The serve loop writes .graqle/govern.health.json atomically after every tick — pipe it into your existing monitoring (Prometheus, Datadog, an oncall dashboard, a simple curl).
Independently verifiable, by anyone. Committed batches anchor to the public Sigstore Rekor transparency log. Any third party can verify a record — auditor, regulator, counter-party — without access to your infrastructure, or ours. Verification doesn't depend on Quantamix staying online.
💰 Token economics — a worked case study
A 4-developer team on a 50,000-node enterprise codebase burns ~$40 per developer per day on flat-file AI-coding tokens in 2026. The same team using GraQle's substrate:
| Flat-file baseline (Cursor / Claude Code default) | $42,240 | — |
| GraQle + frontier API (Sonnet 4.6) | $19,874 | −53% |
| GraQle + local SLM (Year 2, 90% migrated) | $5,174 | −88% |
Every number is auditable. Every assumption is sourced (Anthropic pricing, Cursor power-user data, Microsoft's killed Claude Code pilot, NCBI biomedical-KG research showing >50% token reduction, Qwen3-Coder SWE-Bench benchmarks). Scale linearly to a 40-developer enterprise: ~$224k/year saved in Year 1, ~$371k/year in Year 2.
Plus six things Cursor / Copilot / Codex do not offer at any subscription tier: cryptographic audit trail, EU AI Act Article 26 readiness (€15M fine exposure), patent-defensible substrate, survive-vendor-disappearance, multi-agent governance, public Sigstore Rekor anchoring.
→ Read the full case study — math, sources, and a bash snippet to re-run it on your own team's numbers.
What is GraQle
A governance-led multi-agent reasoning system for code, with a built-in cryptographic audit substrate for the AI you ship to production. Scan any codebase into a persistent knowledge graph. Every module becomes a reasoning agent. Agents decompose, debate, and synthesize answers with clearance-level governance. Every change — and every production decision — is impact-analysed, gate-checked, and cryptographically committed.
AI assistants see files. GraQle sees architecture. That's why it catches the cross-file bugs they can't, and why its audit trail survives every level of tampering.
Built for engineering teams who need:
- Cross-file reasoning — impact analysis, lesson recall, dependency-aware refactor (the kind of thing that requires reading 5 files; we read the graph instead).
- Auditable AI decisions — confidence scores, evidence trails, tamper-evident logs anchored to a public transparency log.
- EU AI Act–aligned behaviour out of the box — for European customers, regulated deployments, and analyst-grade due diligence.
- Model-agnostic operation — 14 LLM backends, offline-capable via Ollama, runs entirely on your machine by default. No telemetry. Code stays on your machine.
How it works
- Scan → AST + dependency analysis builds a typed graph (functions, classes, modules, imports, calls).
- Activate → A pre-reasoning safety layer scores each node for relevance, confidence, and risk before the LLM runs.
- Reason → Multiple agents debate. Outputs carry
confidence, graph_health, active_nodes, evidence pointers.
- Gate → Governance gates (CG-01..CG-20) intercept write-class operations. Plans required. Risks surfaced. Trade-secret + path-traversal hardening enforced.
- Audit → Every tool call is logged to
.graqle/governance/audit/ with redaction + secret scanning.
- Commit → For runtime decisions, the audit record gets canonicalised (RFC 8785), Merkle-rooted (RFC 6962), ed25519-signed, and anchored to the public Sigstore Rekor log.
- Learn → Lessons become weighted edges. The graph remembers across sessions, teams, and git operations.
The pipeline runs through five named phases — ANCHOR → ACTIVATE → GENERATE → VALIDATE → COMMIT. Each phase is governance-gated, evidence-attached, and audit-logged.
API defaults: confidence_threshold=0.65 (refusal floor), gate_threshold=0.60 (gate-status floor). Both are configurable per-call.
Model agnostic
Anthropic · OpenAI · AWS Bedrock · Ollama · Gemini · Groq · DeepSeek · Together · Mistral · OpenRouter · Fireworks · Cohere · Azure OpenAI · custom HTTP.
backends:
reasoning: anthropic/claude-sonnet-4-6
embedding: bedrock/titan-v2
summaries: ollama/llama3
Runs fully offline with Ollama. No telemetry. Code stays on your machine. API keys stay in your local graqle.yaml.
Governance gate — drop-in for Claude Code, Cursor, VS Code
graq init
graq gate-install
graq init writes the GraQle constitution into your project, so your AI tool
behaves like a disciplined senior engineer from the very first command: governed
tools only (every change is checked), a defined investigate → plan → review →
apply → learn workflow, built-in token-cost rules, and the project's known
pitfalls baked in. One rulebook — shipped as
graqle/data/constitution/ — renders for every
client (Claude Code → CLAUDE.md, OpenAI Codex → AGENTS.md, Cursor →
.cursorrules, Windsurf → .windsurfrules), so editing it once keeps them all
in sync.
gate-install then routes every native write/edit/bash through GraQle's governance gates and adds a permissions backstop to .claude/settings.json. Plans required for risky changes. Trade-secret scanning on git commits. Path-traversal hardening on subprocess capture. CG-01 through CG-20 — all on, all auditable.
→ Governance Gate spec
MCP-first
// .mcp/config.json
{ "graqle": { "command": "graq", "args": ["mcp", "serve"] } }
76+ MCP tools — every operation Claude Code / Cursor / VS Code Copilot needs is exposed as a governed tool with confidence scores, evidence pointers, and audit-trail entries. No prompt engineering, no glue code.
🇪🇺 EU AI Act–aligned
Articles 6, 9, 12, 13, 14, 15, 25, 50 become applicable on 2026-08-02. GraQle gives your high-risk AI system the signals, audit trail, and disclosure primitives it needs — so the parts of your compliance file you can quote from us, you can quote today.
graq compliance switch on
graq compliance switch status
graq compliance switch off
graq compliance status
graq compliance export --since 2026-08-01 --sha256-sidecar
graq compliance baseline-doc generate --output baseline.jsonl
graq compliance periodic-assessment run --period-start ... --period-end ...
graq compliance feedback record --rating 5 --note "..."
graq compliance eur-lex-check
| Art 4 — AI literacy | Integration guidance for providers + deployers | Art 4 doc |
| Art 9 — Risk management | Periodic-assessment artefacts with auto-remediation triggers | graq compliance periodic-assessment run |
| Art 11 — Technical documentation | Dated, content-addressed baseline document at deployment | graq compliance baseline-doc generate |
| Art 12 — Record-keeping | JSONL audit export + SHA-256 tamper-detection sidecar | graq compliance export |
| Art 13 — Deployer transparency | graph_health + confidence on every reasoning envelope | every graq_reason call |
| Art 14 — Human oversight | Confidence-gated refusal of auto-apply + claim-limits vocabulary | GRAQLE_EU_AI_ACT_MODE=on + graq edit/apply/auto |
| Art 15 — Accuracy / robustness / cybersecurity | 17 named defences + 7 measurable claims | graq compliance status --include-robustness |
| Art 25 — Value-chain responsibility | Intended-purpose declarations + PCT (Proof-Claims Token) x-ai-eu extension (11 fields) | Art 25 doc + graq pct issue/validate |
| Art 43 — Conformity assessment | Substrate evidence inputs (baseline-doc + audit log + periodic assessment + robustness + Article 14 gate) for the deployer's Annex VI internal-control file | Art 43 doc |
| Art 50 — Transparency for users | Auto banner + ai_disclosure machine field | GRAQLE_EU_AI_ACT_MODE=on |
| Art 72 — Post-market monitoring | graqle govern serve continuous anchoring + graqle govern health snapshot | v0.62.0 |
Three substantive non-claims kept legally clean:
- GraQle is NOT itself a high-risk AI system (no Annex III category applies).
- GraQle is NOT a GPAI provider under Article 51 (we use third-party LLMs, we don't place one on the EU market).
- We provide signals, audit primitives, and conformity-assessment evidence inputs. We never say compliant or certified. The discipline is enforced in code —
TestNonClaimsInvariants blocks any release that introduces a compliant/certified field.
→ Full Article-by-Article mapping in docs/compliance/eu-ai-act/
Contributions welcome on the compliance docs
The EU AI Act docs are deliberately open to contribution — corrections, translations (DE/FR/ES/IT have highest demand), compliance gap reports from deployers building Annex VI internal-control files, and cross-framework mappings (NIST AI RMF, ISO 42001, ENISA, etc.) are all welcome. See CONTRIBUTING-COMPLIANCE.md for the contribution guide, the vocabulary discipline the CI enforces, and what kinds of changes go through which review path.
Security & integrity
| No telemetry | GraQle does not phone home, collect usage data, or send analytics. |
| No code upload | Source never leaves your machine unless you opt in to cloud sync. |
| Secret scanning | 200+ regex patterns + Shannon-entropy detection + AST scan on every output candidate. |
| PyPI Trusted Publishing | OIDC-only — no long-lived API tokens in our pipeline. |
| Sigstore signatures | Every wheel signed by our GitHub Actions identity. Verify with graq trustctl verify --version <v>. |
| CycloneDX SBOM | Attached to every GitHub Release. |
.pth-file guard | Publish pipeline rejects any wheel containing .pth files (the LiteLLM-class attack vector). |
| Reproducible builds | SOURCE_DATE_EPOCH-pinned, rebuild from tagged source and compare checksums. |
| Survive-disappearance | Production audit records anchor to public Sigstore Rekor — verifiable even if Quantamix disappears. |
→ Full disclosure policy: SECURITY.md · Report vulnerabilities to security@quantamixsolutions.com
What's new in v0.75.0
The EU AI Act layer is complete. GraQle now offers an optional, configurable
EU AI Act (Reg. (EU) 2024/1689) compliance layer — off by default, enforced
through a tamper-evident, irreversible latch.
- Configurable + irreversible latch (
governance.eu_ai_act in graqle.yaml):
once enabled, the layer cannot be silently disabled and blocking cannot be
downgraded to advisory. The latch is an ed25519-signed, hash-chained
record (.graqle/eu_ai_act_latch.jsonl) — not a hand-editable flag — so a
tamper attempt fails closed and can never turn it off.
- Enforced compliance phase (CG-EU-AIA) wired into the gate: when enabled,
AIA-relevant write tools pass an Article-14 human-oversight check.
blocking + low confidence → refused with an audited per-action override
path; advisory → recorded + advised, never blocked. Reads, planning, and
reasoning are never gated.
- Light-touch + honest by design — a record-keeping / traceability aid
(supports Art. 12 / 72), not a hard wall, and not a substitute for human
compliance judgement. The latch supports the Act's expectations; it is not
"required by the Act."
This completes GraQle's universal-governance arc (constitution-as-code →
every client → universal server gate → cost-is-observability → EU AI Act layer).
→ Full v0.75.0 changelog
What's new in v0.73.0
Cost is observability, never a quality gate. GraQle never cuts reasoning or
debate quality to save money. Every cost path is now advisory: it measures
and surfaces spend (the cost-savings story) but never halts still-valuable work.
- Reasoning continues past budget to natural convergence /
max_rounds; the
cost of continuing is measured (continuation_cost_usd in result metadata).
- Multi-backend debate no longer stops on budget — it runs to
max_rounds
and reports over-budget rounds instead.
- Advisory per-session cost meter in the MCP server surfaces
session_cost_usd
and a one-time over-budget note — purely observational, never blocks a tool,
and hardened against malformed cost values.
- Runaway protection stays value-based (
max_rounds + the absolute LLM-call
ceiling), never price-based.
→ Full v0.73.0 changelog
What's new in v0.72.0
One constitution, every AI client. The governance rulebook now renders into
every supported client from a single source — including OpenAI Codex via
AGENTS.md, which previously had no instruction file. Run graq init and your
AI tool pair-programs with a disciplined senior engineer from the first command,
whichever tool you use.
- The constitution (
graqle/data/constitution/) — governed-tools-only rules, the 9-phase workflow, the full MCP tool inventory, token-cost rules, learned-behaviour workarounds, and a configurable (off-by-default) EU AI Act section. Modular Markdown; edit once, every client stays in sync.
- Per-client rendering: Claude Code →
CLAUDE.md, OpenAI Codex → AGENTS.md (new), Cursor → .cursorrules, Windsurf → .windsurfrules. Append-under-marker and idempotent — an existing file is never clobbered.
graq gate-install adds a non-destructive permissions backstop to .claude/settings.json (deny native write/exec, allow the governed graq_* tools) behind the existing PreToolUse hook.
→ Full v0.72.0 changelog
Recent releases
- v0.62.0 — Runtime R2:
graqle govern serve continuous anchoring worker + govern health Article-72 monitoring snapshot.
- v0.61.0 — Runtime R1: FastAPI middleware +
@governed decorator. Drop-in governance for any FastAPI app.
- v0.60.0 — Runtime R0 Mode A:
GovernedRuntime.attest() and PII-safe pseudonymize_ref().
- v0.59.0 — Layer 5 cryptographic substrate GA: RFC 8785 canonicalisation + RFC 6962 Merkle commitments + ed25519 signatures + Sigstore Rekor anchoring + local replay queue.
- v0.58.0 — EU AI Act Wave 3 substrate (Article 43 conformity-assessment evidence) + OPSF PCT alignment +
GRAQLE_WORKTREE_ROOT for parallel-worktree dev.
- v0.57.0 — EU AI Act Wave 2:
graq compliance switch single entry-point, Article 14 confidence-gated refusal, claim-limits vocabulary, EUR-Lex drift guard.
→ Full changelog
Pricing
| Free | Local-only graphs · core SDK · governance gates · EU AI Act surfaces · attest() runtime · govern serve anchoring (self-hosted, anchored to public Rekor) |
| Pro — $19/mo | Cloud sync · priority models · hosted Rekor relay |
| Team — $29/dev/mo | Shared KGs · team-wide lessons · audit log retention · SOC 2 evidence pack |
| Enterprise | On-prem · custom backends · dedicated support · regulated-deployment SLAs · contact us |
The free tier is real: the verifier, the runtime attestation path, and the continuous anchoring worker are all in the open-source SDK. Paid tiers add operational scale, team features, and a managed Rekor relay.
Patent & license
Core methods are patent-pending: EP26167849.4 (filed 2026-03-25), EP26162901.8 (CIP), and EP26166054.2 (CogniGraph divisional). The SDK source is fully auditable under the GraQle License — see LICENSE. Reimplementation of the patented methods outside this SDK requires a separate patent license.
→ github.com/quantamixsol/graqle — issues, discussions, contributions welcome.