Chris Lucas | AI Consulting & Legacy Code Modernization

About Chris Lucas

AI consultancy delivering end-to-end AI product development and automation. My expertise covers discovery and requirements, system design, implementation, deployment, and stakeholder reporting -- primarily in Python and on Google Cloud.

I specialize in LLM-enabled solutions such as RAG (retrieval-augmented generation), vector databases, document ingestion and chunking, and chat interfaces. I build practical systems that turn unstructured knowledge into searchable, reliable assistants for support, learning, and internal operations.

RAG & Vector Database Systems
LLM Integration (OpenAI, Anthropic, Mistral, Gemini)
Python & Google Cloud Architecture
Multi-language Support with DeepL
University Lecturer & Corporate Trainer

12+

AI Projects

15+

Years Digital

4

Universities

6+

Countries

Services

Practical AI solutions tailored to your business needs

Legacy Modernization

Transform legacy codebases with AI agents. RAG-powered documentation, automated code analysis, intelligent refactoring pipelines, and developer support chatbots built on your existing systems.

AI Training & Workshops

Hands-on training for developers and executives. From 'vibe coding' workshops with AI-assisted IDEs to university-level courses on AI-powered business development and automation.

AI-Ready Processes

Design and implement AI-ready infrastructure: document ingestion pipelines, vector databases, chat interfaces, translation workflows, and analytics dashboards -- all on Google Cloud.

Engagement Process

A structured path from assessment to full implementation

Phase 1 -- 2 Weeks

Assessment & Discovery

Deep dive into your existing systems, codebase audit, stakeholder interviews, and identification of high-impact AI integration opportunities. Deliverable: strategic roadmap with prioritized recommendations.

Phase 2 -- 2 Months

Pilot Implementation

Build and deploy a working proof-of-concept on the highest-value use case. RAG system setup, LLM integration, chat interface, and initial user testing. Real results, fast feedback.

Phase 3 -- 1-6 Months

Full Program Rollout

Scale the solution across teams and systems. Production hardening, team training, analytics setup, and ongoing optimization. Knowledge transfer ensures your team owns the result.

Selected Projects

Real-world AI solutions delivered end-to-end

RAG Platform

Solana Developer Support

Full RAG-powered Q&A platform for Solana Superteam UK. YouTube transcript ingestion, file upload support, Google Drive integration, and Telegram chatbot.

Python RAG Google Cloud Telegram DeepL

RAG Platform

Corvinus University Learning Platform

AI-powered learning assistant for university students. Large material chunking, web and Telegram chat interfaces, multi-language support, and anonymized analytics for instructors.

Python RAG Google Cloud DeepL

AI Training

University AI Course

Designed and delivered an AI-powered business development course at Corvinus University Budapest. Students built real AI products using RAG, LLMs, and cloud services.

Python Google Cloud RAG LLM

RAG Platform

Legal Document Assistant

Document analysis system for a London law firm. Automated contract review, clause extraction, and risk assessment using RAG and fine-tuned models.

Python RAG Google Cloud LLM

Automation

Translation Pipeline

Automated multi-language translation workflow for a European NGO. Document ingestion, DeepL integration, quality assurance, and publishing pipeline.

Python DeepL Google Cloud

RAG Platform

Internal Knowledge Base

Enterprise knowledge management system for a fintech startup. Slack integration, document ingestion from Confluence and Google Drive, and conversational search.

Python RAG Google Cloud Slack

AI Training

Vibe Coding Workshops

Interactive workshops teaching developers to leverage AI-assisted IDEs. Cursor, Copilot, and Claude Code for rapid prototyping and code generation.

Cursor Copilot Claude VS Code

Automation

Analytics Dashboard

Real-time analytics dashboard for monitoring AI system performance. Usage tracking, cost analysis, quality metrics, and stakeholder reporting.

Python Google Cloud BigQuery

RAG Platform

Customer Support Bot

AI-powered customer support chatbot for an e-commerce platform. Product knowledge base, order tracking integration, and multilingual support.

Python RAG Google Cloud Telegram

Latest from the Blog

Insights on AI, business development, and technology

Tech

Building RAG Systems That Actually Work

Lessons learned from deploying RAG-powered assistants across universities, corporations, and developer communities. What chunking strategies, embedding models, and retrieval techniques make the biggest difference.

June 15, 2025 3 min