AI integrations

We integrate AI capabilities into existing products and platforms - from intelligent search and document processing to decision-support systems built for regulated industries.

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AI works best when it solves one clear problem inside a system that already runs well.

We add AI to products and platforms where it genuinely helps. Document processing, smart search, workflow automation, and AI-assisted decisions. We test carefully, especially for industries where accuracy matters. We do not add AI just because it sounds good. We add it where it actually makes a difference.

  • We check if AI is the right solution before we build anything

  • Works with your existing systems, nothing needs to be rebuilt

  • Tested for accuracy including unusual cases and failure scenarios

  • Built to be auditable for industries with strict compliance requirements

How an engagement works

Every project follows the same three steps

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Step 1: Scope and plan

Typically 1 to 3 wks

We learn about your business and define exactly what we are building before any work begins.

Conversations with your team to understand the problem

Review of any existing systems or assets

Written scope covering deliverables and timeline

Agreement on what success looks like

Pricing Icon

Step 2: Design and build

The majority of the project

We do the work in stages with regular check-ins so you can see progress and give feedback.

Work delivered in clear stages, not all at once

Regular reviews so you stay informed and in control

Testing throughout, not just at the end

Open communication if anything needs to change

Pricing Icon

Step 3: Deliver and hand over

Final 1 to 2 weeks

We finish, check everything works, and make sure your team has everything they need to take it forward.

Final quality checks before anything goes live

Full documentation of what was built and how it works

Handover to your team with training where needed

Clear next steps if ongoing support is required

Pricing Icon

Step 1: Scope and plan

Typically 1 to 3 wks

We learn about your business and define exactly what we are building before any work begins.

Conversations with your team to understand the problem

Review of any existing systems or assets

Written scope covering deliverables and timeline

Agreement on what success looks like

Pricing Icon

Step 2: Design and build

The majority of the project

We do the work in stages with regular check-ins so you can see progress and give feedback.

Work delivered in clear stages, not all at once

Regular reviews so you stay informed and in control

Testing throughout, not just at the end

Open communication if anything needs to change

Pricing Icon

Step 3: Deliver and hand over

Final 1 to 2 weeks

We finish, check everything works, and make sure your team has everything they need to take it forward.

Final quality checks before anything goes live

Full documentation of what was built and how it works

Handover to your team with training where needed

Clear next steps if ongoing support is required

Pricing Icon

Step 1: Scope and plan

Typically 1 to 3 wks

We learn about your business and define exactly what we are building before any work begins.

Conversations with your team to understand the problem

Review of any existing systems or assets

Written scope covering deliverables and timeline

Agreement on what success looks like

Pricing Icon

Step 2: Design and build

The majority of the project

We do the work in stages with regular check-ins so you can see progress and give feedback.

Work delivered in clear stages, not all at once

Regular reviews so you stay informed and in control

Testing throughout, not just at the end

Open communication if anything needs to change

Pricing Icon

Step 3: Deliver and hand over

Final 1 to 2 weeks

We finish, check everything works, and make sure your team has everything they need to take it forward.

Final quality checks before anything goes live

Full documentation of what was built and how it works

Handover to your team with training where needed

Clear next steps if ongoing support is required

We say no to AI projects where the data is not good enough, the problem is not clear, or the accuracy needed cannot realistically be achieved. That is not us being difficult. It is us making sure you do not spend money on something that works in a demo but causes problems in real use.

Smidja,

on why we are careful about which AI projects we take on