AI by Design: Spark

You’ve got the right AI use cases, now you need proof they actually work.
Spark turns concepts into working prototypes, pressure-tests them with real users, and shows you what’s ready to scale and what needs rethinking before you commit serious time or budget.

What’s inside Spark

A rapid, structured process to turn AI use cases into working prototypes and test them with real users:

Prototype scoping

Ethics by design

Rapid prototyping

User testing

Prototype evaluation

Scale readiness review

When Spark might be what you need

When you’ve defined clear use cases and need validation before investing

When leadership wants evidence that an idea will deliver value

When you need to de-risk technical, usability, or adoption risks early.

Spark

What we do

We define what each prototype needs to prove, build functional AI prototypes, and test them with users to assess value, usability, and scale readiness. 
Timeline: 3–6 weeks

Starting at

$50,000

What you get

Working AI prototypes with core features that users can interact with and test.

User testing findings highlighting what users valued, where they struggled, and what to refine.

A scale-readiness assessment outlining which concepts are worth scaling and the requirements to implement them.

Assumption:

Development of up to 3 functional prototypes.

Up to 4 interviews per prototype for user feedback.

Excludes recruitment cost and incentives.

Phase 1: Scoping & Design

Prototype Scoping & Ethics by Design

We define what each prototype needs to prove — and ensure ethics is built in from the start.

Define scope for each prototype: what problem it solves, what success looks like, what's in and out of scope.
Map data needs, technical constraints, and test audiences.
Embed ethics early through bias checks, transparency, and user control.

Phase 2: Governance & Roadmapping

Rapid Prototyping & Development

We build functional prototypes users can actually interact with.

Develop working prototypes focused on core AI functionality.
Build only what’s required to validate the concept effectively.

Phase 3: User Testing & Evaluation

User Testing & Validation

We observe real users in action to understand what works and what breaks.

Test prototypes with end users.
Capture behaviour, confusion points, and moments of value.
Gather feedback on usability, clarity, and usefulness.

Prototype Evaluation & Readiness Review

We evaluate what’s ready to scale and what isn’t.

Assess which prototypes delivered real value.
Identify what must change before moving to implementation.
Define technical, operational, and adoption requirements.

Your team

Who you'll have on the team

Lead Strategist

To define prototype scope, set success criteria, shape responsible-AI considerations, and ensure each prototype tests the right value and business outcomes.

Design Researcher(s)

To design and observe user testing sessions, capture real behaviour, uncover friction and value moments, and translate insights into clear prototype refinements.

AI & Data advisor

To assess data readiness, evaluate model and system feasibility, identify technical constraints, and outline what’s needed to scale a validated prototype.

Where are you in your AI journey?

Start with the challenge you're facing right now. Take what you need or go the full path.