AI agents that do multi-step work, with a human where it counts
An AI agent is a system that takes a goal, works through several steps to reach it, and uses tools along the way: reading documents, looking up prices, drafting a reply. We build agents for small businesses that do real work, such as answering technical product emails from a supplier's own parts and price lists, with a person reviewing before anything is sent.
What this looks like in practice
An industrial equipment supplier needed technical product emails answered faster. Every inquiry required a specialist to look up parts, check price lists, and re-type similar answers. We built an AI email response agent grounded in their parts lists, price lists, and product documentation. Inbound inquiries get accurate, sourced draft responses, and a specialist reviews the draft instead of writing from scratch.
Other agents we build research a topic, analyze a dataset, or prepare a first draft of content, each with a review step sized to the stakes.
What makes an agent trustworthy
- Grounding: the agent answers from your documents and cites them, rather than from general knowledge
- Boundaries: a defined set of tools and a defined set of actions, nothing open-ended
- Review: a human approves before anything leaves the building, until the agent has earned more autonomy
- Logging: every step recorded, so a wrong answer can be traced and fixed
How we build it
We start with one narrow job the agent will do well, build it on n8n or in Python, and connect it to the documents and systems it needs. We test it against real past inquiries, not demo data. The agent goes live in draft mode first. Autonomy expands only when the review log shows it is ready.
Tools we use
n8n, Anthropic Claude, OpenAI, Python, Pinecone, your email and document systems.
Questions we hear
Will the agent send wrong answers to customers?
Not without a person approving them. Every agent we ship starts in review mode, and most stay there for the steps where a mistake would cost you a customer.
How long does an agent take to build?
A first agent doing one narrow job typically goes from discovery call to running in review mode in weeks, not months. The timeline depends mostly on how organized the source documents are.