Where AI agents pay off first
- Support: answering questions from your own documentation and handing off with context when a person is needed.
- Sales: qualifying enquiries, drafting replies and updating the CRM.
- Documents: reading invoices, contracts or forms and extracting the fields your systems need.
- Internal knowledge: an assistant that answers staff questions from policies, SOPs and past tickets.
- Operations: checking data, flagging exceptions and preparing reports for a person to approve.
Chatbot, automation or agent?
A chatbot answers questions. Automation follows fixed rules. An agent combines both: it understands a request, decides which tools to use and completes the steps. Many problems only need plain automation, and we start there when it is enough, because it is cheaper and fully predictable.
Accuracy you can measure
Before launch we build a test set of real questions with expected answers and measure the agent against it. Answers cite their sources, low-confidence cases go to a person, and every action is logged, so you can see what the agent did and why.
Your data stays under control
We choose the model per use case: hosted APIs such as OpenAI, Anthropic or Gemini, Azure OpenAI for enterprise agreements, or self-hosted open models when data must not leave your infrastructure. On their business API plans, these providers do not train on your data by default.
Built from daily experience
We run our own AI assistant on this website and ship an AI chatbot plugin for WordPress, so we deal with the practical problems — cost per conversation, wrong answers, rate limits and lead capture — every day.
