5 GitHub repositories for legal teams: setup and running costs

8 min read

These GitHub projects help legal teams draft documents, find files, collect signatures and review contract text. This guide is for lawyers, legal operations staff and the technical colleagues helping them choose and install a tool for a specific task.

Most need technical help to install. Once running, four offer browser-based workflows; eyecite is a Python library. These are documentation-based setup notes, not results from our testing.

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Choose the task

Repository	Use case	Stars	Licence	Biggest catch
docassemble	Guided intake and document assembly	985	MIT	Someone must keep the legal wording and rules current
Paperless-ngx	Searchable document archive	47.1k	GPL-3.0	The application doesn’t encrypt stored information
DocuSeal	Document filling and signing	18.8k	AGPL-3.0, with additional terms	Some features sit in the paid Pro tier
eyecite	US legal citation extraction	295	BSD-2-Clause	It finds citations but doesn’t check them
OpenContracts	Contract annotation and structured extraction	1.5k	MIT	A platform to configure, not a tool to switch on

Before installing

GitHub hosts the code, README instructions and licence. Downloading a ZIP does not install the application. Use the project’s documented installation route. Docker packages software and its dependencies; Docker Compose starts several connected services together. You need Docker installed before running Docker commands.

Use public sample files for the first trial. The commands below are starting points for a technical colleague, not complete production deployment instructions.

1. docassemble: document assembly

What it does: docassemble collects answers through a questionnaire and fills Word or PDF templates. Use it for intake forms and repeatable agreements with approved clauses.

You need: Docker, a machine to run it and someone comfortable with YAML and Python to build the questions and branching rules.

1. Follow the official Docker guide using the jhpyle/docassemble image. Configure storage and access for the trial.
2. Create a short interview for fictional party names and dates, then attach an approved template.
3. Generate documents using different answer combinations. Check every field and conditional clause.

Expected result: a questionnaire that produces a populated document. The software does not supply your approved legal wording or decision rules.

Running costs: hosting, maintenance and template development. Legal staff must update the wording when requirements change.

2. Paperless-ngx: searchable files

What it does: Paperless-ngx indexes documents and uses optical character recognition (OCR) to make scanned text searchable.

You need: Docker Compose, document storage and backups. The setup guide recommends PostgreSQL for new installations.

1. From the official setup guide, download the Compose file for your chosen database, plus docker-compose.env and .env. Save the Compose file as docker-compose.yml.
2. Configure storage paths and environment settings, then run the commands below from that directory.
3. Complete user setup in the guide. Import public PDFs, including a scan, and search for phrases you have checked in the originals.

docker compose pull
docker compose up -d

Expected result: a browser-based archive with searchable documents. Missed or incorrect OCR text needs checking against the scan.

Running costs: server, storage and backups. The README warns that the application does not encrypt stored information; protection depends on the deployment.

3. DocuSeal: PDF signing

What it does: DocuSeal adds fields to PDFs and routes them to people for completion and signing.

You need: Docker for a local trial. A shared deployment also needs configured access, storage and email.

1. Create an empty trial directory. Run the command below there; it stores application data in that directory and restricts the published port to this computer.
2. Open http://localhost:3000, complete setup and upload a sample PDF.
3. Assign name, date and signature fields to test participants. Complete the workflow and inspect the finished PDF and signing records.

docker run --name docuseal -p 127.0.0.1:3000:3000 -v "$PWD":/data docuseal/docuseal

Expected result: a local signing application. This adapts the README command for local access; use its deployment instructions for a shared HTTPS service.

Running costs: hosting, email and administration, or a commercial cloud plan. SSO, reminders and roles are listed as Pro features. Confirm the signing requirements for your documents and jurisdiction separately.

4. eyecite: US citations

What it does: eyecite extracts legal citations from text. It is aimed at American citation patterns, not primarily German or EU authorities.

You need: Python, pip and basic scripting skills. Install it in a separate Python environment:

python -m pip install eyecite

Run this small example in Python:

from eyecite import get_citations

text = "See 1 U.S. 12."
for citation in get_citations(text):
    print(citation)

Expected result: extracted citation objects printed in the terminal. Next, compare a public passage against citations marked by hand. PDF files need text extraction before this function can process their contents.

Running costs: integration and maintenance. The basic example needs no model API key. It does not check whether an authority supports an argument or remains good law.

5. OpenContracts: clause annotation

What it does: OpenContracts organises document collections, labels passages and supports structured extraction.

You need: Git, Docker Compose and developer support. Its Quick Start below creates a development environment.

1. Follow the official Quick Start to clone the repository and copy the three sample environment files into .envs/.local.
2. From the repository directory, build and start the services with the commands below.
3. Open http://localhost:3000. Replace the documented default credentials, keep the instance private and create a collection of public contracts. Label termination and renewal passages manually before trying extraction.

docker compose -f local.yml build
docker compose -f local.yml --profile fullstack up

Expected result: a development platform for document annotation, not a configured legal reviewer. You supply the labels and check the extracted results.

Running costs: developers, infrastructure and optional model or embedding services. Review connected providers and document visibility before using confidential material.

Access controls also need an owner. Our reporting on AI mental-health services and conversation privacy shows why a reassuring interface is not enough: buyers still need to establish who can read sensitive records and who responds when a risk is flagged.

What to measure

Record setup hours, time to a checked result, corrections and monthly running costs. Compare that with the existing process on the same sample documents. Our build or buy guide covers the wider decision. Find more projects in the IC Lab GitHub repository hub.

Methodology and sources

Official repositories and setup documentation checked 25 October 2026. Commands are documented steps or explicitly identified adaptations; Industry Contents did not execute them. Suggested trials and setup effort are editorial judgements. No performance or maintenance-time measurements were taken.

• docassemble on GitHub and its documentation.
• Paperless-ngx on GitHub.
• DocuSeal on GitHub.
• eyecite on GitHub.
• OpenContracts on GitHub.

For another team, our guide to GitHub repositories for marketing covers setup, trial tasks and running costs.

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