Process first. Then the right tool.

Most stalled AI projects sit on top of a process nobody fixed. We look at how the work gets done before we pick the tool.

Not everything needs AI.

Four questions, in this order, on every brief.

01

Fix the process

Remove the steps, handoffs and rework first. Often the biggest win costs nothing.

02

Use what exists

If an off-the-shelf tool does the job, we set it up and move on.

03

Build what is missing

Custom software where nothing fits, built to be handed over.

04

Add AI where it pays

Only where it saves real time or improves a decision, with a person in charge.

How a project runs.

Each step ends with something you can see and a decision you make.

Step 1

Diagnose

Map how the work really happens and where it breaks.

  • Time with the people doing it
  • Process and data mapping
  • Baseline agreed
Step 2

Decide

Process change, existing tool, custom build or AI.

  • Options with costs
  • Quick wins first
  • Measures agreed
Step 3

Build and prove

On your data, on real work, against the baseline.

  • Working version early
  • Approval steps designed in
  • Results measured
Step 4

Hand over

So it holds after we leave.

  • Your team trained
  • Runbooks and handover
  • Next use case scoped

Ways to work with us.

Scope and price are agreed in writing before work starts. Longer programmes are priced against milestones.

Programmes

Delivery partner in a consortium

We lead the AI product, data and delivery workstream inside a wider bid or programme, alongside universities, regional bodies and larger suppliers.

Talk about a bid
Fixed scope

Pilot

A defined use case, taken to a working version on real data with agreed success measures.

Scope a pilot
Ongoing

Product and delivery leadership

Senior leadership for an AI product or platform, through build, launch and adoption.

Discuss leadership

Questions worth asking.

Not always. Often the bigger win is fixing how the work flows, or using a tool you already pay for. We will tell you when AI is not the answer.
We start from the workflow and the outcome you need, not from a product. Where an existing tool fits, we use it. Where it does not, we build, on your data and in your systems.
In your cloud or on your premises. When data must stay on site we use local models, so nothing leaves the building. Personal data is kept out of any system that does not need it.
Ownership of code, data and any new IP is agreed in writing before work starts, not discovered at the end.
We lead the AI product, data and delivery workstream inside a wider programme, alongside universities, regional bodies and larger suppliers. We are used to shared plans, shared reporting and other people's governance.
For a defined use case, a first working version on real data in weeks, not months. Larger programmes run as a series of these, each with its own measures.
Scope and price are agreed in writing before work starts. Longer programmes are priced against milestones.

Have something to deliver?

Tell us the outcome you need. We will tell you whether it needs AI, and how we would get there.

Start a conversation Or email hello@plushstreet.com