Modern AI delivery workspace with teams coordinating intelligent product workflows

An AI consultancy that engineers how firms operate

We rebuild the workflows your business runs on, so AI handles the repetitive part and your team keeps the judgement. The platform underneath already exists, so we start on your workflow rather than on infrastructure.

What actually changes

Every engagement is aimed at one of these. If it is not, it is not worth building.

Repetitive work stops being human work

Document handling, data entry, triage, and reporting move to systems that record what they did and pass on anything they should not decide.

Work stops waiting on people

Anything that sat in a queue for someone to read, route, or retype now moves while your team is doing something else.

You take on more without hiring for it

Volume grows without a matching line in the headcount plan, because the work it creates does not grow with it.

Customers get the same answer every time

Response quality stops depending on who picked the request up and how busy they were that day.

What we do

Three kinds of work. All of it starts with a workflow you already run.

What is running today

Four working systems, running in real businesses. Named where the client agreed.

Grants & Funding

From call discovery to submission-ready applications. Running at Apply Consulting.

Marketing Engine

Strategy, research, writing, design, review, all as a coordinated team. Running at Sidekick and firstsignals.ai.

Field Service

Enquiry to invoice to compliance, with the messaging and scheduling wired in.

Competitive Intelligence

Market scans, competitor analysis, positioning research, delivered as premium briefs.

All four run on Bureau, the operating layer we set up and manage for each firm. Auth, roles, audit trails, and cost tracking already live there, which is why an engagement starts at your workflow rather than at infrastructure. Bureau is delivered through Clarvia. There is no self-serve version.

Explore Bureau

How we keep it under control

AI work can move quickly. It still needs somewhere for the risk to go.

How we work in detail

We agree the risk before we build

Every engagement starts by writing down where AI can act on its own, where a person has to check it, and which data never goes near the model.

Security is part of the acceptance criteria

Prompt injection, data leaks, weak tool permissions, and unsafe fallbacks are tested before launch, not patched after.

One workflow first

We agree what working means before we build it, ship one bounded workflow, measure it, and expand from there.

You get the system, not a dependency

Architecture notes, monitoring, runbooks, access boundaries, and named ownership all transfer at handover.

Tell us the workflow. We will tell you if AI should touch it.