AI Development Services & Intelligent Solutions

A statistical model trained on billions of text tokens that can read, summarise, write, translate and reason. GPT-4o, Claude 3.5, Llama 3 and Gemini are LLMs.

Connecting an LLM to your private documents so it answers using your data, not just what it was trained on. The most common production LLM pattern in 2026.

Continuing the training of a pre-trained model on your own data so it learns your tone, format or domain vocabulary. Cheaper than RAG for very narrow tasks.

Numeric fingerprints of text, images or audio that let a computer measure how similar two things are. The plumbing behind every RAG search and recommendation engine.

An LLM wrapped in a loop that can plan, call external tools (APIs, search, your CRM) and decide what to do next without a human at each step.

A model that handles more than one input type — text, image, audio, video — in the same prompt. GPT-4o and Gemini are multimodal.

AI that produces new content — text, images, code, audio — instead of just classifying or scoring existing data. Includes LLMs, Stable Diffusion, voice cloning.

The discipline of writing instructions that consistently get the behaviour you want from an LLM. In production it's evaluation + iteration, not clever phrasing.

A database optimised to store and search embeddings. Pinecone, Weaviate, pgvector and Qdrant are the most common production choices.

DevOps for ML models: training pipelines, version control, monitoring, drift detection and rollback. Without it, ML doesn't survive contact with production traffic.