DocketVault

Consent-Aware Legal Intake Vault — Turn scattered personal data into lawyer-ready evidence packs, with full client control over what gets shared.

DocketVault is a permissioned data pipeline and secure vault built for legal intake. Clients upload evidence (documents, images, audio), AI extracts and organizes it into a structured timeline, and attorneys receive a complete evidence pack — only after the client explicitly approves sharing.

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Key Features

• Client-private vault — uploads are private by default; attorneys see nothing until the client approves
• AI-powered extraction — Claude analyzes images/PDFs, Whisper transcribes audio, structured data is extracted automatically
• Timeline & categorization — events are placed on a timeline with categories, summaries, and gap detection
• Consent-gated sharing — clients preview, approve/exclude, and can revoke access at any time
• Evidence Pack export — attorneys export a ZIP with summaries, indexes, files, hashes, and audit trails
• Append-only audit log — every view, share, export, and revoke is recorded

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Tech Stack

Layer	Technology
Backend API	FastAPI, SQLModel, PostgreSQL, Alembic
Async Workers	Celery + Redis
AI / LLM	Anthropic Claude (extraction & enrichment), OpenAI Whisper (audio)
Frontend	Streamlit
Auth	JWT + bcrypt, Google OAuth (Drive/Gmail/Calendar)
Storage	Local filesystem (dev) or S3-compatible (prod)

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Prerequisites

• Python 3.10+
• PostgreSQL 15+ — brew install postgresql@15
• Redis — brew install redis && brew services start redis
• API Keys (optional for basic demo):
  • ANTHROPIC_API_KEY — Claude-powered extraction & enrichment
  • OPENAI_API_KEY — Whisper audio transcription

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Quick Start

1. Clone & set up the database

git clone https://github.com/sainikkam/docketvault.git
cd docketvault

brew services start postgresql@15
createdb docketvault

2. Install backend dependencies

cd backend
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

3. Configure environment variables

cp ../.env.example .env

Edit backend/.env with your values:

DATABASE_URL=postgresql+asyncpg://<your-user>@localhost:5432/docketvault
STORAGE_BACKEND=local
JWT_SECRET=change-me-in-production
ANTHROPIC_API_KEY=sk-ant-...
OPENAI_API_KEY=sk-...
REDIS_URL=redis://localhost:6379/0

4. Run database migrations

make migrate

5. Launch (3 terminals)

Terminal 1 — FastAPI backend:

cd backend
source .venv/bin/activate
uvicorn app.main:app --reload --port 8000

Terminal 2 — Celery worker (AI extraction):

cd backend
source .venv/bin/activate
celery -A app.worker worker --loglevel=info

Terminal 3 — Streamlit frontend:

cd streamlit
pip install -r requirements.txt
streamlit run streamlit_app.py --server.port 8501

Open http://localhost:8501 in your browser.

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Docker (Optional)

For PostgreSQL and Redis only (the app itself runs locally):

docker compose up -d

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Project Structure

docketvault/
├── backend/
│   ├── app/
│   │   ├── auth/           # JWT auth, user registration, roles
│   │   ├── matters/        # Legal matters (cases) CRUD
│   │   ├── firms/          # Law firm management
│   │   ├── evidence/       # Evidence artifact storage
│   │   ├── extraction/     # AI extraction (Claude + Whisper)
│   │   ├── enrichment/     # Timeline, categorization, gap analysis
│   │   ├── sharing/        # Consent-gated sharing & revocation
│   │   ├── exports/        # Evidence Pack ZIP generation
│   │   ├── notifications/  # In-app notifications
│   │   ├── oauth/          # Google OAuth connectors
│   │   ├── gmail/          # Gmail import
│   │   ├── main.py         # FastAPI app entry point
│   │   ├── worker.py       # Celery worker config
│   │   └── config.py       # App settings
│   ├── requirements.txt
│   └── Makefile
├── streamlit/
│   ├── streamlit_app.py    # Main app & navigation
│   ├── pages/              # One file per page (login, upload, review, etc.)
│   └── lib/                # Shared helpers (API client, session, theme)
├── persona_p01/            # Sample persona data for testing
├── demo/                   # Demo RFP / scenario files
├── docker-compose.yml      # PostgreSQL + Redis containers
└── .env.example            # Template for backend/.env

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Demo Walkthrough

1. Register an attorney account and a client account
2. Attorney creates a firm, template, and matter, then sets up evidence requests with AI-generated checklists
3. Attorney generates an invitation token and shares it with the client
4. Client joins the matter using the token
5. Client uploads evidence (images, PDFs, audio) — AI extraction runs automatically in the background
6. Client reviews the AI-generated timeline, extracted data, and missing items
7. Client approves sharing (with per-item control and sensitivity flags)
8. Attorney views the dashboard, browses approved evidence, and exports the Evidence Pack

See LAUNCH_GUIDE.md for the full step-by-step walkthrough.

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Makefile Commands

make dev        # Start FastAPI dev server
make migrate    # Run Alembic migrations
make test       # Run pytest
make lint       # Ruff check + format check
make format     # Auto-format with ruff

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API Documentation

FastAPI auto-generates interactive docs at http://localhost:8000/docs when the backend is running.

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License

All rights reserved.