Staff who never sleep and never quit
We build AI agents and embed them in your processes: answering customers, handling inbound requests, content, reporting, campaign monitoring. An agent is not a scripted chatbot — it’s a worker that takes a task through to a result.
MODES FROM OUR OWN PRACTICE — WE RUN THE AGENCY ON AGENTS OURSELVES
| Property | A scripted chatbot | An AI agent |
|---|---|---|
| An unexpected question | “Sorry, I didn’t get that — pick a menu item” | Works out what’s actually being asked and answers it |
| A multi-step task | Can’t do it | Plans the steps itself and carries them through |
| Working with your data | Only hard-coded answers | Reads your database, CRM, documents and spreadsheets |
| Oversight | Nothing to oversee | An action log plus human sign-off on the steps that matter |
- Support agent — answers customers by email and messenger 24/7; hands hard cases to a person with a draft reply already written.
- Sales agent — qualifies enquiries, answers questions, follows up to payment, keeps the CRM current.
- Marketing agent — daily monitoring of ad accounts, reporting, drafts of posts and campaigns.
- Analyst agent — pulls numbers from web analytics, CRM and the bank into one summary and flags anomalies.
- Content agent — articles, posts, product cards, video scripts, in your tone of voice.
Deployment rules — without them an agent is dangerous
- Honesty guarantees: the agent doesn’t hide its errors and doesn’t invent data — this is verified by tests before launch.
- Limits of authority: what the agent does on its own and what needs human sign-off is written down.
- Action log: every step the agent takes is recorded, so any answer can be checked.
- Economics: before deployment we compare the hourly cost of that routine done by a person against the cost of the agent.
Map the routine
We look at where your team’s hours actually go and price that routine per month. Then we pick the process that pays back fastest.
Pilot on one process
We build the agent, connect it to your data and run it on real tasks alongside a person. Then we compare quality and speed.
Launch with oversight
The agent goes “on shift” with an action log and sign-off rules. For the first weeks a person checks everything; after that, spot checks.
Scale
Once the first agent has paid for itself, we add the next processes. The team works on meaning, the agents on routine.
Shall we price what your routine actually costs?
Describe the one process that eats the most time — we’ll come back with a payback calculation for an agent and a pilot plan.
Request the calculation> we run on agents ourselves: this website was built by them, under human supervision