AI automation and AI agents that take real work off your team

An AI agent is software that uses a large language model to complete multi-step tasks within rules you define, such as reading an enquiry, looking up information in your systems, updating your CRM and drafting a reply for review. Unlike a simple chatbot it can take actions, so we add limits, logs and human approval points.

Cost depends on the use case, the number of systems involved, how much of your data needs preparing, the guardrails and review steps required, and expected usage. Model usage is billed by the AI provider on your own account. We start with a prototype on your real data so you can judge quality before a full build.

We design against it. Answers are grounded in your own content through retrieval, the model is instructed to say when it does not know, and unclear or sensitive questions are handed to a person. Before launch we test with real customer questions, and after launch we review conversations to fix weak answers.

Mostly OpenAI GPT models and Anthropic Claude models, chosen per task for quality, speed and cost; for simple classification we may use smaller, cheaper models. We keep the model choice behind a clean interface, so you can switch providers later without rebuilding the automation.

We use API access, which OpenAI and Anthropic do not use to train their models by default, keep data and keys in your accounts, and send only the data each task needs. Sensitive fields can be masked before they reach the model, and every action is logged so you can audit what happened.

A focused assistant or single-task agent can go from prototype to production in a few weeks once the content and access are ready. Agents that touch several systems or need approval steps take longer. We agree the first use case, test it on real data, then launch it with monitoring and a plan for improvements.