You will get Legal Document Automation Pipeline — Built in 72 Hours
Project details
Most law firms are still copy-pasting data into Word templates by hand — slow, error-prone, and impossible to scale. I build automated pipelines that take raw case data (PDF uploads, web forms, or structured input) and produce court-ready legal documents in seconds, not hours.
Every pipeline I build is production-grade: field extraction with GPT-4, structured data validation, template population, and clean Word/PDF output. No hallucinations, no missing fields — just consistent, compliant documents at scale.
I've built multi-agent document pipelines for legal motions businesses producing hundreds of filings per month. I specialize in US practice areas with strict formatting requirements: bankruptcy, immigration, and family law.
If your current process involves anyone copy-pasting into a template, I can automate it. Send me a message with your document type and I'll tell you exactly how I'd build it.
Every pipeline I build is production-grade: field extraction with GPT-4, structured data validation, template population, and clean Word/PDF output. No hallucinations, no missing fields — just consistent, compliant documents at scale.
I've built multi-agent document pipelines for legal motions businesses producing hundreds of filings per month. I specialize in US practice areas with strict formatting requirements: bankruptcy, immigration, and family law.
If your current process involves anyone copy-pasting into a template, I can automate it. Send me a message with your document type and I'll tell you exactly how I'd build it.
AI Algorithms
Large Language Model, Transformer ModelAI Applications
Natural Language Generation, Natural Language UnderstandingAI Development Language
PythonAI Models
GPT-4, LLaMAWhat's included
| Service Tiers |
Starter
$500
|
Standard
$1,500
|
Advanced
$2,500
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | - | - | - |
Batch Normalization | - | - | - |
Database Integration | - | - | - |
Detailed Code Comments | - | - | - |
Image Upscaling | - | - | - |
MLOps | - | - | - |
Model Deployment | - | - | - |
Model Documentation | - | - | - |
Model Monitoring | - | - | - |
Model Testing & Optimization | - | - | - |
Model Tuning | - | - | - |
Natural Language Processing | - | - | - |
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | - | - | - |
Setup File | - | - | - |
Source Code | - | - | - |
Frequently asked questions
About Onyeukwu
Custom AI Agent Builder | Chatbots, Automation & LLM Systems
Ejigbo, Nigeria - 10:52 pm local time
Here's what I've shipped:
- Built a multi-agent pipeline for a legal motions business: raw case data → field extraction → template population → court-ready output.
- Built a multi-agent system for a commercial insurance agency: policy research, coverage comparison, quote generation, and client intake — end to end.
- Built a programmatic SEO agent for a fintech client that autonomously creates, optimizes, and publishes content at scale.
Stack: Claude, GPT-4o, LangChain, n8n, Make, Python, FastAPI, Retell, Voiceflow — I work with whatever the project requires. No tool lock-in.
My edge is what I call expertise on demand: every agent I build starts with a domain intelligence protocol — a structured knowledge architecture built specifically for your business. Your competitors have chatbots. Yours will have operational depth.
Every project I take on is delivered in 48-72 hours. Fixed-price milestones. Scope defined upfront. No surprises.
Minimum engagement: $500. If you need a $50 bot, I'm not your person. If you need something that actually works inside your business, send me your use case. I'll tell you exactly how I'd build it before you spend a dime.
Steps for completing your project
After purchasing the project, send requirements so Onyeukwu can start the project.
Delivery time starts when Onyeukwu receives requirements from you.
Onyeukwu works on your project following the steps below.
Revisions may occur after the delivery date.
Requirements intake & document analysis
Review your document type, existing templates, and input data format. Confirm scope and field extraction strategy.
Pipeline build & testing
Build GPT-4 extraction layer, template engine, and end-to-end pipeline. Validate output against your sample documents and fix edge cases.