Topic cluster

Machine learning and generative AI

RAG, fine-tuning, agents and assistants explained for the people who sign off the budget.

Pillar guide

Machine Learning Development Services: The Complete Business Guide

The pillar guide to buying ML: use-case selection, the delivery lifecycle, MLOps expectations, cost bands and how return is actually measured.

Consideration
AI Agents: The Realistic Guide to Business Automation
Agents are workflow software with a probabilistic core. The architecture, approval gates and observability that make them safe, and the processes to start with.
12 min read
Awareness
Large Language Models Explained for Business Leaders
What an LLM is, in language a board can act on: capability, cost, failure modes, vendor lock-in and the governance questions to ask before deployment.
10 min read
Consideration
Fine-Tuning vs RAG: Which AI Approach Should Your Company Use?
A decision matrix across cost, accuracy, freshness and maintenance, plus the hybrid pattern most mature teams end up with.
11 min read
Consideration
RAG Architecture Explained: Building AI Apps With Your Own Data
A full RAG reference: chunking strategies, hybrid retrieval, reranking, citation, caching, evaluation, and the seven mistakes that make RAG look bad.
13 min read
Consideration
How Companies Build Internal AI Assistants That People Actually Use
Most internal assistants die of low adoption, not bad models. The architecture, permission model and adoption design that keep usage above 50%.
12 min read

Next step

A ninety-minute session with the engineers who would build it. You leave with an architecture opinion and a costed next step.