metrwnos chatbot | Mohamed Yosef

The problem

Most people who contact a law firm are not ready to hire a lawyer yet. They have a question: about a contract, a dispute, an inheritance, and they want a quick, understandable answer before committing to a paid consultation. For a small firm like Meter we Nos, answering those questions manually eats into billable time, and ignoring them loses potential clients.

Why a chatbot, and why now (Nov 2024)

A year ago this would have been a hard sell. Generic chatbots gave generic answers, and no law firm can afford a bot that improvises legal advice. What changed in 2024 is that retrieval-augmented generation became practical and cheap: the model answers from the firm’s own indexed legal documents instead of its imagination, and fast, low-cost models like Gemini Flash make per-query costs negligible.

The business case is simple:

First contact runs 24/7. Prospective clients get an immediate answer in Egyptian Arabic instead of waiting for office hours.
Lawyers stop repeating themselves. The most common questions get consistent answers drawn from the firm’s own material, freeing lawyer time for cases that actually need a lawyer.
Better-qualified consultations. By the time someone books a session, the basics are already covered, so the intake queue fills with real cases rather than FAQ traffic.

System & Architecture

Built as a contract AI engineering project around a Retrieval-Augmented Generation (RAG) pipeline:

LLM & Embeddings: Google Gemini (gemini-1.5-flash) through LangChain’s RetrievalQA.
Vector Retrieval: FAISS index over a corpus of Egyptian legal documents.

What I did

Designed and implemented the RAG pipeline end to end: document indexing, vector retrieval, and answer generation.
Wrote the system prompt so responses come back as clear Egyptian Arabic legal explanations, suitable for talking to clients rather than lawyers.
Built the Streamlit prototype and the client intake flow around it.

Demo Walkthrough

The demo below (v0.3) shows the chatbot answering Egyptian legal questions and walking through the intake flow:

Outcome

Delivered a working prototype through three demo iterations (v0.1 to v0.3), enough to show the firm that document-grounded LLMs can realistically handle legal intake for a boutique practice.