Legal document automation for firms, finance teams and SaaS
Legal and finance work still runs on documents: contracts to send and sign, statements to turn into numbers, research to dig through, and exports that have to look right. I build the pipelines that read, generate and move those documents, with AI where it helps and plain code where it’s safer.
- Serverless LaTeX→PDF at Podiam AI
- LegalEase AI for MindsDB Quest 019
- Local-first RAG with DocuMind
Documents are where the hours go
In legal, finance and back-office teams, the slow part is rarely the decision. It is retyping a bank statement into a spreadsheet, rebuilding the same PDF by hand, chasing a signature, or searching a pile of files for one clause. Each step is small and easy to get wrong, and each one can be automated with checks that catch the mistakes a tired person misses.
Legal research and data extraction
LegalEase AI is a semantic legal research assistant I built for MindsDB Quest 019 with MindsDB, Gemini and Ollama, served by Flask in Docker. It searches by meaning rather than exact keywords. PDF2CSV-AI converts PDF bank statements into clean CSV with deep-learning table extraction. DocuMind is a local-first RAG assistant where retrieval runs entirely on-device, so documents never leave the machine.
Generating, exporting and signing documents
At Podiam AI I replaced a local LaTeX dependency with a serverless LaTeX-to-PDF pipeline with multi-API fallback, and unified PDF, DOCX and Markdown export into one reusable React component over a TypeScript layer. I also traced LangChain provider metadata leaking into customer-facing documents back to the persistence boundary. For PowerSmith Energy the server generates PDF commission statements, so reps and the office hold the same document.
- Serverless LaTeX to PDF with fallback providers
- One export component for PDF, DOCX and Markdown
- DocuSign plus PDF and Excel exports in OnOffDeals
Privacy and correctness first
Legal and financial documents are sensitive, so I default to the least exposure that still works: local-first retrieval where it fits, role-based access with JWT, and storage you control on AWS S3 or Cloudflare R2. For AI output I use structured outputs and validation, so malformed or missing fields are caught before they reach a document. I don’t give legal advice; I build the tooling your professionals rely on.
Rates from $20/hour
Hourly for open-ended work, fixed price for defined projects. The first call is free and there's no obligation.
Frequently asked questions
What kinds of legal document automation can you build?
Research assistants that search documents by meaning, PDF data extraction into CSV, PDF and DOCX generation, export pipelines and DocuSign signing flows. I have built each of these in projects such as LegalEase AI, PDF2CSV-AI, Podiam AI and OnOffDeals.
Can our documents stay on our own machines?
Yes, where the use case allows. DocuMind, my local-first RAG assistant, runs retrieval entirely on-device so documents never leave the machine. For cloud setups I keep files in your own AWS S3 or Cloudflare R2 storage and limit who can read what.
Can you fix an existing document pipeline instead of rebuilding it?
Usually, yes. At Podiam AI I joined a production Django and Next.js codebase, split one reported bug into three independent defects and fixed each with its own test. I reproduce the problem, isolate it and write up the cause before changing code.
How is pricing handled?
Rates start from $20/hour. For a defined job, such as converting a batch of bank statements or adding DocuSign to an app, I quote a fixed price. Book a free 30-minute call with a sample document and I will tell you what is realistic.