Get your own AI agents. Your team does more, and it costs less.

Agents handle the routine. Your people keep the decisions, and their time goes to the work that matters.

IThe pile

Every week starts with the same pile.

Invoices to enter. Supplier emails to answer. Order numbers copied from one screen into another. The same question from a customer, answered by hand for the tenth time.

None of it is hard. All of it takes the hours you meant to spend on the work only you can do.

Overhead view of a desk covered in invoices, opened envelopes, receipts and sticky notes beside a coffee cup and a laptop. — **Fig. 1** A normal Monday. Nothing here needs a person, and a person does all of it.

So hand it over.

**Fig. 2** The same desk, before and after the agent.

Chapter III · The handover

An agent reads the pile, does the work, and hands you the result.

Chapter III · The handover

You check one folder, not fifty sheets.

The agents we build read the email, find the invoice, enter it, file it and draft the reply. Anything unusual comes back to you to decide.

IVKept close

Your documents stay yours.

We build retrieval systems that search your own files from inside your own account. Every request passes an access check, every answer cites where it came from, and every step is logged.

We also research how AI systems get attacked and how private data leaks out of them, so the defences in your system come from our own work, not a checklist.

Fig. 3 Where your data goes, and where it never goes.

VTalk to your data

Your business already knows the answers.

Every order, invoice, email and customer record you have kept is a record of what works and what does not. Most of it sits in spreadsheets and old systems nobody has time to read.

We build a private AI chat on top of it. Ask a question in plain words and it answers from your own records: a short explanation, a chart when numbers help, and a suggestion for what to do next. It runs on your data, inside your account, like everything else we build.

23×more likely to clearly beat competitors at winning new customers

19×more likely to reach above-average profitability

Companies that use their customer data intensively, compared with those that do not. McKinsey DataMatics survey of 400 senior managers, 2014. In an MIT study of 179 large firms (Brynjolfsson, Hitt and Kim, 2011), companies that make decisions from data were 5 to 6 percent more productive.

Talk to your data Sample

Suggestion

Fig. 4 A working sample: the answers are computed on this page from an invented shop's records, not from real customer data.

Chapter VI

What we build

Six kinds of work, each built around how your business already runs.

A neat stack of paper in an open blue folder.

AI agents

An agent for one repeated job, done end to end and handed back for your approval.

Email · invoices · orders · scheduling

A printed bar chart with one blue bar circled in pencil.

Talk to your data

A private AI chat over your own records. Ask in plain words, get answers, charts and next steps.

Sales · customers · stock · trends

A closed grey steel document box with its key beside it.

Secure document search

Ask questions of your own files. Answers cite the source and respect who may see what.

RAG · access control · audit log

A magnifying loupe on a printed page, one line underlined in blue.

AI security research

We test how models fail under attack and design systems that keep private data private.

Model audits · adversarial testing · privacy

A closed laptop, a phone and a tablet laid out neatly.

Custom apps

Software built for one business, on the devices your team already uses.

iOS · Android · Windows · Mac · Linux

Nested white and grey desk trays stacked in orderly tiers, one tray blue.

AI platforms

The ground under your models: deployment, monitoring and the APIs your apps call.

MLOps · monitoring · APIs

Not sure which you need? Describe the pile. We will tell you.