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06

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

01

Knowledge Bot

Company docs → instant answers from your own data

02

Workflow Automation

AI agents that trigger, reason and act autonomously

03

Semantic Search

Meaning-based search across large document sets

04

AI-Powered Features

Embed LLM capabilities into any existing product

Let's build something smart

Chatbot, RAG system, automated workflow — let's scope it.

Get in Touch