Questions beforeyou shortlist.

That's the raw model, the one part you already had. A bare seat has no skills, no memory, and nothing wired into the systems your work lives in, which is why it changed nothing. 78% of people using AI at work brought the tool themselves (Microsoft and LinkedIn, 2024). We install the rest, inside something your compliance team has approved.

A service that includes the software, rather than software with services attached. We scope it, build it in your own cloud account, run it, and report what it returned. The code, the rules and the data are yours. The underlying pattern stays ours, and nothing of yours ships to another client.

That's most of the job. The incumbent stays authoritative, write-back goes through its own API, and every write is read back and logged. Where a system has no API, an agent operates it the way your staff do, under approval.

You are. You can't sue a model, but you can hold a named person and a named process to account. So the limits are agreed in scoping and then sit in the system connections and the approval steps. Anything written into a prompt can be talked around.

We are not insurance advisers, and how your policy responds is a question for your broker rather than for us. What we can tell you is that through 2026 professional-liability insurers started writing AI exclusions into E&O and D&O wordings, and that what these policies turn on is who reviewed the work. So we build the review lane first and the automation behind it: a named person approves anything that leaves, on a hash-chained ledger you can export and put in front of your broker. Last checked August 2026.

Enterprise endpoints where your obligations allow, open-weight models served in the UK or Canada, or fully inside your own cloud account, which is also the Canadian residency answer. Changing the model later means re-testing it on your samples, so we schedule that as work rather than flipping a setting.

Put the four questions above to them. The tell is the second one: if the before-number came from the vendor's own model rather than from someone measuring the work while the old way was still running, the saving is a quote and not a measurement. It might still be right. Neither of you can check it.

Harper raised $46.8m in February 2026 to run AI-native commercial insurance broking for mid-sized businesses. Lawhive raised a €50m Series B as an AI-native law firm. Both are funded to serve your clients directly, and both are UK-facing. The part of the work that stays yours is the judgement, and your people only get to spend their time there if the document-heavy end stops taking their week.