AI Engineering
Turning raw AI into intelligent systems
I integrate LLMs, build RAG pipelines and connect vector databases — making AI actually useful for your specific domain.
How RAG Works
Your Data
Docs, PDFs, DBs
Embeddings
Vectorise content
Vector DB
Pinecone / Milvus
LLM
OpenAI / local
Answer
Accurate & grounded
What I Do
Prompt Engineering
Chain-of-Thought & Few-Shot design that maximises LLM precision and minimises hallucinations.
RAG Pipelines
Connect LLMs to your own knowledge base for accurate, domain-specific answers.
Vector Databases
Efficient semantic search with Pinecone & Milvus.
LangChain Integration
Composable chains, agents and memory layers built for production.
Workflow Automation
AI-powered pipelines with n8n — connect tools, APIs and LLMs into smart, autonomous workflows.
Conversation Design
Intent recognition, fallback strategies and context management for reliable AI conversations.
Use Cases
Knowledge Bot
Company docs → instant answers from your own data
Workflow Automation
AI agents that trigger, reason and act autonomously
Semantic Search
Meaning-based search across large document sets
AI-Powered Features
Embed LLM capabilities into any existing product
Let's build something smart
Chatbot, RAG system, automated workflow — let's scope it.