Converting Static Documentation into Autonomous Governance
Documentation sits in folders gathering dust. Developers make costly mistakes because they can't manually cross-reference every governance rule in a 50-page policy doc for every feature they build. The result: compliance rework, security incidents, and project delays.
AutoAlign turns static policy documents into a living, autonomous governance system.
┌─────────────────────────────────────────┐
│ AutoAlign Architecture │
└─────────────────────────────────────────┘
┌──────────┐ ┌──────────────────────────────────────────────────────┐
│ Policy │────▶│ Knowledge Base (ChromaDB) │
│ Docs │ │ Internal_Recommendation_Doc.md + Data Dictionary │
└──────────┘ └────────────────────────┬─────────────────────────────┘
│ RAG Retrieval
▼
┌──────────┐ ┌──────────────────────────────────────────────────────┐
│ BRD │────▶│ LangGraph Workflow │
│ (Input) │ │ │
└──────────┘ │ ┌─────────────┐ violations ┌──────────┐ │
│ │ DEFENDER │ ─────────────────▶ │ DRAFTER │ │
│ │ AGENT │ ◀───────────────── │ AGENT │ │
│ │(Policy │ revised BRD │(Architect│ │
│ │ Guardian) │ │ Solution)│ │
│ └──────┬──────┘ └──────────┘ │
│ │ compliant / max iterations │
│ ▼ │
│ ┌─────────────┐ │
│ │ REPORT │ │
│ │ NODE │ │
│ └─────────────┘ │
└──────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────┐
│ Aligned BRD + Report │
│ (Output) │
└─────────────────────────┘
- Defender Agent analyzes the BRD against the policy knowledge base via RAG, identifying all violations
- If violations exist, Drafter Agent rewrites the BRD to fix every issue while preserving business intent
- The revised BRD goes back to the Defender for another pass
- Loop continues until the BRD is compliant or max iterations are reached
- Final Compliance Report is generated with full audit trail
| Component | Technology |
|---|---|
| AI Reasoning | Google Gemini 1.5 Pro (high context window for large Markdown files) |
| Vector Storage | ChromaDB (local) / Vertex AI Vector Search (production) |
| Data Warehouse | BigQuery (audit logs, policy metadata) |
| Orchestration | LangGraph (multi-agent state machine) |
| SDK | Turgon SDK (AutoAlign integration layer) |
| Embeddings | Google embedding-001 |
| Framework | LangChain |
AutoAlign/
├── main.py # CLI entry point
├── requirements.txt
├── .env.example
├── config/
│ ├── __init__.py
│ └── settings.py # All configuration
├── src/
│ ├── agents/
│ │ ├── defender.py # Policy Defender Agent
│ │ └── drafter.py # Compliance Drafter Agent
│ ├── knowledge_base/
│ │ ├── loader.py # Document ingestion + vector store
│ │ └── retriever.py # RAG retrieval
│ ├── workflow/
│ │ ├── state.py # LangGraph state definitions
│ │ └── graph.py # Multi-agent workflow graph
│ └── utils/
│ └── logger.py # Structured logging
├── turgon/ # Turgon SDK (high-level client)
│ ├── client.py
│ └── models.py
├── docs/ # Policy documents (knowledge base)
│ ├── Internal_Recommendation_Doc.md
│ └── Data_Dictionary.md
└── examples/
└── sample_brd.md # Intentionally non-compliant BRD demo
git clone https://github.com/aakash4dev/AutoAlign.git
cd AutoAligncp .env.example .env
# Edit .env and add your GOOGLE_API_KEYGet a Google AI Studio API key: https://aistudio.google.com/app/apikey
# Create a virtual environment
python3 -m venv .venv
# Activate it
source .venv/bin/activate
# Install dependencies
pip install -r requirements.txt
# Start the backend API server (runs on http://localhost:8000)
uvicorn api.server:app --reload --port 8000Keep this terminal open. The backend must be running for the frontend to work.
Open a new terminal and run:
cd frontend
npm install
npm run devThe frontend will start on http://localhost:3000.
You can also use AutoAlign directly from the command line without the frontend:
# Activate the virtual environment (if not already)
source .venv/bin/activate
# Align the sample BRD (which has intentional violations)
python main.py align examples/sample_brd.md
# Save the aligned output
python main.py align examples/sample_brd.md --output aligned_brd.md
# Query the policy knowledge base directly
python main.py query "What are the rules for storing customer IDs in logs?"
# Rebuild the knowledge base (after adding new policy docs)
python main.py rebuild-kbThe examples/sample_brd.md contains a real-world BRD with intentional violations:
| Violation | Policy | Severity |
|---|---|---|
customer_id stored in plaintext logs |
Section 4.2 (PII) | CRITICAL |
user_email stored in plaintext |
Section 4.2 (PII) | CRITICAL |
ip_address in plaintext |
Section 4.1 (PII) | CRITICAL |
| API key hardcoded in source code | Section 5.3 (Secrets) | CRITICAL |
CORS wildcard * in production |
Section 2.2 (API Security) | HIGH |
| No authentication on debug endpoint | Section 2.1 (Auth) | HIGH |
| No rate limiting | Section 2.2 (API Security) | HIGH |
| Shared service account with admin access | Section 2.1 (PoLP) | HIGH |
| Service account key committed to Git | Section 5.3 (Secrets) | CRITICAL |
| Indefinite data retention | Section 4.2.3 (Minimization) | MEDIUM |
FLOAT type for currency |
Data Dictionary | MEDIUM |
AutoAlign automatically detects and fixes all of these.
from turgon import TurgonClient
client = TurgonClient(max_iterations=5)
# Align a BRD string
result = client.align(brd_text)
# Align a BRD file
result = client.align_file("examples/sample_brd.md")
print(result.status) # ComplianceStatus.COMPLIANT
print(result.compliance_score) # 1.0
print(result.aligned_brd) # The fixed, compliant BRD
print(result.compliance_report) # Human-readable report
print(result.summary()) # One-liner summary
# Query the knowledge base
answer = client.query_policy("What are PII logging rules?")
print(answer)- GitHub PR Integration: Hook AutoAlign into GitHub Actions to auto-check every PR
- Multi-Domain Support: Legal, HR, GDPR, DPDP Act, SOC 2 policy sources
- Vertex AI Vector Search: Production-scale vector store with real-time updates
- BigQuery Audit Warehouse: Full audit trail of every alignment decision
- Slack/Teams Notifications: Real-time compliance alerts for developers
| Member | Role |
|---|---|
| Aakash Singh Rajput | Lead AI Developer (Agentic Workflows) |
| Tushar Kumar | Cloud Architect (GCP Integration) |
| Nandini Goyal | Host and Engagement Lead at OSCG |
| Shivani Sahu | Full Stack Developer |
Event: HackFest 2.0 — GDG Cloud New Delhi Track: Agentic AI
AutoAlign makes policy invisible and compliance inevitable.