An AI agent understands a request and then acts on it in your systems: it checks an order, opens a support ticket, updates a customer record or books a visit. We design each agent around a short list of allowed actions, log everything it does, and hand anything risky to a person.
An AI agent is software that uses a language model to understand a request, decide which of its allowed tools to use, and carry out the steps, for example reading an order from your store system and replying with the tracking link. Unlike a chatbot, it can change things in your systems, which is why its permissions, limits and handoff rules matter as much as the AI itself.
Customers get order status, delivery dates or account details after their identity is checked.
The agent gathers the details, creates the ticket in the right queue and tells the customer what happens next.
Contact details, call notes and deal stages updated from emails and conversations, ready for a person to confirm.
Appointments booked, moved or cancelled against your real availability.
Details collected and checked, a draft quote prepared, and a person asked to approve it.
Agents that check stock, chase missing paperwork or prepare reports from several systems.
Users describe a job in plain words or drop in contracts, invoices and scans. The assistant reads them, asks for what’s missing and builds a draft case against a checklist. Rules do most of the reading, an LLM fills only what they can’t, and nothing is saved until a person confirms it.
Read the case study →An AI agent checks orders, shares tracking and opens tickets in the help desk. Refunds and exceptions go to a person with the case already prepared.
See how it works →Requests from email and web forms are sorted by type and urgency, routed to the right team with a draft reply, and summed up for managers each week.
See how it works →Only within limits. Each agent gets a short list of allowed actions, approval steps for anything risky, and a full log. Most agents start with a person approving each action until the results justify more freedom.
Classic automation follows fixed steps. An agent can handle requests worded in many different ways and choose the right step, but it does so inside the same kind of fixed limits.
Anything with an API or a reliable import format: CRMs, help desks, store platforms, calendars, accounting tools and your own databases. The assessment confirms what your systems allow.
The assessment is free. A prototype agent that handles one job in a test environment is a fixed $2,900 for 2 weeks. Running, monitoring and improving it starts at $3,500 a month.
Risky actions need approval, so mistakes are caught before they happen. Every step is logged, we review the logs monthly, and you can switch the agent off at any time.
Tell us what you have in mind. The first conversation and the assessment are free.
