graqle
Connects with Git workflows to trigger automatic intelligence recompilation and maintain audit trails of architectural changes.
Supports Google Gemini as a backend for performing low-cost semantic queries and architectural reasoning.
Extracts architectural metadata, including functions, classes, and call graphs, from JavaScript source files to build the knowledge graph.
Provides integration for JetBrains IDEs through a CLI and Python SDK for developer intelligence and architecture querying.
Parses Markdown documentation to extract decisions, requirements, and stakeholders for integration into the codebase knowledge graph.
Offers an optional Neo4j backend for high-performance graph storage, supporting large-scale codebases with vector search and proximity analysis.
Allows for local, zero-cost LLM reasoning by using Ollama as a backend provider for graph-based queries.
Leverages OpenAI models to provide sophisticated reasoning and context-aware insights about codebase architecture.
Integrates as a pre-commit governance gate using the DRACE framework to verify data quality and reasoning accuracy before code changes.
Deeply analyzes Python codebases to extract module structures and dependencies while offering a native SDK for programmatic graph interaction.
Compatible with the Replit environment via CLI and SDK for managing and querying architecture-level intelligence.
Analyzes Rust source code to identify module hierarchies and dependency patterns for inclusion in the architecture knowledge graph.
Parses TypeScript code to extract detailed architectural insights, including module imports and class relationships.
Uses YAML for flexible server configuration and task-based routing across multiple LLM backends.
GraQle — EU AI Act–aligned reasoning for code
The first developer reasoning SDK that ships a structured EU AI Act compliance surface — Article-by-Article, version-pinned, CI-pinnable. Scan any codebase into a knowledge graph. Every module becomes a reasoning agent. Every change is impact-analysed, audit-logged, and disclosure-ready.
pip install graqle && graq scan repo . && graq run "find every security bug in this codebase"Website · EU AI Act docs · VS Code Extension · PyPI · Changelog
🇪🇺 EU AI Act–aligned (v0.58.0, Wave 3 substrate)
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.
# One switch flips every EU-AI-Act-aware subsystem at once
graq compliance switch on # shell snippet → eval to enable
graq compliance switch status # what's actually armed, in one envelope
graq compliance switch off # symmetric disable
# Per-subsystem CLI surface
graq compliance status # legacy + new subsystems block
graq compliance export --since 2026-08-01 --sha256-sidecar # Article 12 evidence
graq compliance baseline-doc generate --output baseline.jsonl # Q16.1 baseline
graq compliance periodic-assessment run --period-start ... --period-end ... # Q16.3
graq compliance feedback record --rating 5 --note "..." # Q16.5 observation
graq compliance eur-lex-check # weekly drift guardArticle | What GraQle ships | Where |
Art 4 — AI literacy | Integration guidance for providers + deployers | |
Art 9 — Risk management | Q16.3 periodic-assessment artefacts with auto-remediation triggers |
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Art 11 — Technical documentation | Q16.1 dated, content-addressed baseline document at deployment |
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Art 12 — Record-keeping | JSONL audit export + SHA-256 tamper-detection sidecar |
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Art 13 — Deployer transparency |
| every |
Art 14 — Human oversight | Confidence-gated refusal of auto-apply + R25-EU11 claim-limits |
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Art 15 — Accuracy / robustness / cybersecurity | 17 named defences + 7 measurable claims |
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Art 25 — Value-chain responsibility | Intended-purpose + PCT (Proof-Claims Token) | Art 25 doc + |
Art 43 — Conformity Assessment | Substrate evidence (baseline-doc + audit log + periodic assessment + robustness + Article 14 gate) for deployer's Annex VI internal-control file | Art 43 doc (since v0.58.0 / cr-019) |
Art 50 — Transparency for users | Auto banner + |
|
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 and audit primitives. We never say compliant or certified. The discipline is enforced in code —
TestNonClaimsInvariantsblocks any release that introduces acompliant/certifiedfield.
→ 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.
What is GraQle
A governance-led multi-agent reasoning system for code. 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 is impact-analysed, gate-checked, and taught back — automatically.
AI assistants see files. GraQle sees architecture. That's why it catches the bugs they can't.
Built for high-end engineering teams who need:
Cross-file reasoning that LLMs can't do alone (impact analysis, lesson recall, dependency-aware refactor).
Auditable AI decisions with confidence scores, evidence trails, and tamper-detectable logs.
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.
Two surfaces, one substrate — govern how your AI is built, and what it decides
GraQle is an EU AI Act–aligned governance substrate with two deployment surfaces on the same engine (knowledge graph → governed trace → RFC 6962 Merkle → ed25519 → Sigstore Rekor):
Build-time (author surface) | Run-time (production surface) | |
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 |
Status | GA | substrate GA in v0.59.0; capture middleware on the roadmap (see ADR-221) |
Run-time, today (v0.59.0): every governed decision your deployed system makes can be
canonicalised (RFC 8785), committed to a Merkle batch (RFC 6962), ed25519-signed, and
anchored to the public Sigstore Rekor transparency log — so anyone can detect tampering
of an audit record with no access to your infrastructure. The batcher adds 0 ms to the
write path (commit is asynchronous). A runnable, end-to-end walkthrough on a real use case
(a loan decision → lock → Merkle → sign → anchor → auditor verifies → tamper detected →
key revoked) ships in examples/.
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 proof
# 1. Scan any codebase into a knowledge graph
graq scan repo .
# → 5,579 nodes, 19,916 edges — full architecture mapped in seconds
# 2. Ask GraQle to audit it
graq run "find every authentication bypass risk"
# → Graph-of-agents activates across 50 nodes
# → Traces cross-file attack chain: MD5 (models.py) → expired tokens
# never checked (auth.py) → cancel endpoint with zero auth (app.py)
# → Confidence: 0.89 | Evidence: 3-file chain | Cost: ~$0.001
# 3. Fix it — GraQle shows exact before/after for each file
# 4. Teach it back — the graph never forgets
graq learn "cancel endpoint must require admin auth"
# → Lesson persists. Every future audit activates this rule.How it works
Scan → AST + dependency analysis builds a typed graph (functions, classes, modules, imports, calls).
Activate → Pre-reason 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.Gate → Governance gates (CG-01..CG-20) intercept write-class operations. Plans required. Risks surfaced.
Audit → Every tool call is logged to
.graqle/governance/audit/with redaction + secret scanning.Learn → Lessons become weighted edges. The graph remembers across sessions, teams, git operations.
Model agnostic
Anthropic · OpenAI · AWS Bedrock · Ollama · Gemini · Groq · DeepSeek · Together · Mistral · OpenRouter · Fireworks · Cohere · Azure OpenAI · custom HTTP.
# graqle.yaml — smart task routing
backends:
reasoning: anthropic/claude-sonnet-4-6 # quality work
embedding: bedrock/titan-v2 # cheap + fast
summaries: ollama/llama3 # local + freeRuns fully offline with Ollama. No telemetry. Code stays on your machine. API keys stay in your local graqle.yaml.
Governance gate — activate full GraQle autonomy
graq gate-install # one-time, project-localRoutes every native write/edit/bash through GraQle's governance gates. 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.
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.
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 |
CycloneDX SBOM | Attached to every GitHub Release. |
| Publish pipeline rejects any wheel containing |
Reproducible builds |
|
→ Full disclosure policy: SECURITY.md · Report vulnerabilities to security@quantamixsolutions.com
What's new in v0.58.0
Current release: v0.58.1 — a documentation-only patch that refreshes this landing page to surface the v0.58.0 feature set (the package is byte-identical to v0.58.0).
EU AI Act Wave 3 substrate + OPSF PCT alignment. Four built-and-sentinel-approved items, all backward-compatible (functionally byte-identical to v0.57.4 in the default/unconfigured state — the new capability surface is inert until activated):
GRAQLE_WORKTREE_ROOTenv var (cr-016) — the MCP server path resolver now honours this as the highest-priority project-root source, unblocking parallel-worktree development forgraq_write/graq_generate/graq_edit. Unset = byte-identical to v0.57.4.Audit-log record schema v2 + content-addressed
policy_version(cr-017) — everyGovernedTracerecord carriesschema_versionand a SHA-256policy_versionbinding to the active baseline-doc; the samepolicy_versionis the 11th field on thex-ai-euPCT extension (OPSF PCT v0.1 Comment 4 alignment). Absent/Nonefields serialise identically to v0.57.4.Article 43 conformity-assessment docs (cr-019) — new
docs/compliance/eu-ai-act/article-43-conformity-assessment.mdmapping GraQle's substrate to Annex VI internal-control requirements, plusCONTRIBUTING-COMPLIANCE.mdinviting docs corrections, translations (DE/FR/ES/IT), and cross-framework mappings.OPSF PCT v0.1 alignment (cr-021) — release-notes plumbing aligning the shipped engineering with the OPSF PCT public-comment window.
The cryptographic tamper-evidence layer (RFC 6962 Merkle commitments + Sigstore Rekor external anchoring) ships next as v0.59.0.
What's new in v0.57.0
EU AI Act Wave 2 — closes 9 of 10 marketing-vs-built gaps (CG-MKT-01..10), bringing the honesty score from 78/100 to ~98/100. Six new compliance modules + one consolidated visibility surface:
graq compliance switch on|off|status— single UX entry-point for the EU AI Act mode toggle.switch statusshows every EU-AI-Act-aware subsystem (Article 50 disclosure, Article 14 gate, claim-limits, baseline-doc, periodic-assessment, feedback-trend, EUR-Lex guard) in one envelope.Article 14 human-review enforcement —
graq edit/apply/autorefuses auto-apply when confidence < threshold (default 0.75, placeholder pending R25-EU-CALIB-01) AND EU AI Act mode is on. Structured refusal envelope witharticle_14_clauses: ["14(4)(c)", "14(4)(d)"].R25-EU11 claim-limits v1.0 — typed vocabulary (17 canonical values, 6 categories) on every governance record. L08 SHACL + L19 audit-trail enforcement. Public attribution to Ricky Jones (TrinityOS).
VERITAS Q16.1 baseline-doc generator —
graq compliance baseline-doc generateproduces a dated, content-addressed artefact (SHA-256). Maps to EU AI Act Article 11 + ISO 42001 Cl. 6.2.VERITAS Q16.3 periodic-assessment —
graq compliance periodic-assessment runwith auto-remediation triggers. Maps to Article 9 + ISO 42001 Cl. 9.1.VERITAS Q16.5 OBSERVATION-ONLY drift watcher —
graq compliance feedback record/ingest+ Welford running statistics. Patent-novelty boundary enforced by mandatory AST audit test per Q-PATENT 2026-05-22.EUR-Lex weekly drift guard —
graq compliance eur-lex-check+ GitHub Actions workflow re-fetches every cited EUR-Lex URL every Monday, opens issue on regulator-side drift.PCT (Proof-Claims Token) Use B —
graqle.pct.issuer/validator+x-ai-euextension namespace (10 fields). First-public-draft of the OPSFx-ai-eunamespace authored by Quantamix.
Prior v0.56.0 surface preserved: all 7 Article docs + CLI surfaces remain. Schema version stays at "1" — graq compliance status --format json is backward compatible (new eu_ai_act_subsystems field is additive).
Pricing
Tier | What you get |
Free | 500-node graphs · 3 reasoning queries / month · unlimited graph viz · core SDK · governance gates · EU AI Act surfaces |
Pro — $19/mo | Unlimited nodes · unlimited queries · cloud sync · priority models |
Team — $29/dev/mo | Shared KGs · team-wide lessons · audit log retention · SOC2 evidence pack |
Enterprise | On-prem · custom backends · dedicated support · regulated-deployment SLAs · contact us |
Patent & license
Core methods are patent-pending (EP26167849.4, EP26162901.8). 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.
GraQle is built by Quantamix Solutions. Graphs that think. EU AI Act–aligned by design.
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