Intelligence
Useful because it knows your company.
Most companies have already tried AI. The disappointment is usually the same: an assistant in a separate tab, brilliant at general questions and useless about the business. The difference isn't the model — it's the context it can reach. That context is a consequence of the work that comes first: understand how the company operates, connect what it runs on, and intelligence finally has something real to reason about.
In practice
The same questions you ask people today.
These are answers drawn from a company's own projects, hours, invoices and documents. Nothing here needs a new tool — it needs an environment where the information already sits together.
Try a question
Reads: projects · time logs · budgets · staffing
Our position
Five principles we don't bend.
Use AI when it makes the business better, not because AI exists. Useful in most of this work. The point of none of it.
01
AI is only as useful as the business context it can see
A general model knows the world. Yours needs to know that Meridian's contract renews in June and that Nadia ran the last three studies for them. The intelligence layer works from your own projects, clients, capacity, documents, financial information and operating history — subject to the permissions your business defines. That context is what a connected operating environment gives it, and why an assistant working inside one is a different proposition from the assistant in a separate tab.
02
Automate the mechanical, keep the judgement
We automate the parts of a process that have one correct outcome: moving a record, generating a draft, extracting a date, sending a reminder. Anything requiring judgement stops for a human, with the reasoning shown.
03
Never a black box
Every answer cites the records it came from. If your COO can't verify a number in two clicks, they won't trust it, and they'd be right not to.
04
Prove the value, then build it
We propose AI where we can point to the work it removes. If a well-designed screen or a simple rule solves the problem, we build that instead — it's cheaper for you and more reliable in practice.
05
Boundaries by design
The assistant respects the same permissions as the rest of the platform. Nobody sees, through AI, what they couldn't see directly. Your data stays yours and isn't used to train anyone's model.
Where it earns its place
Concrete uses, not categories.
Search that finds the answer, not the filename
“What did we conclude about pricing sensitivity for mid-market clients?” returns the finding and the study it came from, not a list of filenames.
Reporting without assembly
The Monday management pack written from live records, in your format, ready for a human to review rather than build.
Document intelligence
Contracts, invoices and forms read on arrival: key dates, values and obligations extracted into the record automatically.
Project summaries
Thirty days of activity on an account compressed into six lines before you walk into the meeting.
Operational recommendations
“This project's burn rate is tracking 9% ahead of delivery” — surfaced while it's still fixable.
Institutional knowledge
A new hire can ask how the firm usually handles something, and get the honest, precedent-based answer.
Automation
The quiet half.
Most of the hours a connected environment gives back have nothing to do with AI.
They come from not entering the same client three times, from an invoice that drafts itself out of approved hours, from a reminder that fires before a deadline instead of after it, and from a report that exists on Monday morning because it was generated overnight.
This work is unglamorous and enormously valuable. We design it first, then ask where intelligence adds something the rules can't.