Two weeks to a working prototype

Validate your AI idea before committing to full development. Prove value, identify blockers, and reduce risk. All in a focused, time-boxed engagement.

Start a prototype

Don't invest millions in an AI system before proving it works

The graveyard of failed AI projects is filled with systems that seemed promising in a slide deck. Data quality issues emerge only when real data touches the model. Latency requirements turn out to be harder than expected. User workflows don't adapt to AI outputs the way the business case assumed.

Rapid AI Prototyping surfaces these realities before you've committed to full development. Two weeks of focused work with real data produces a working prototype. Not a demo, not a mockup. Something that shows exactly what the system can and can't do.

What the prototype delivers

Working end-to-end system

A functional prototype that processes real data, produces real outputs, and handles real edge cases. You can interact with it, show it to stakeholders, and see exactly where it succeeds and where it struggles.

Accuracy benchmarks

Measured performance on your actual data with clear accuracy metrics. Not marketing claims. Real numbers that show whether the approach works at the accuracy level your business requires.

Risk assessment

Documented findings on data quality issues, technical blockers, accuracy gaps, and integration challenges. You know exactly what needs to be solved before full-scale development.

The ASP difference on every engagement

AI-only expertise

We don't do web apps on the side. Every engineer on your project has deep AI specialisation and has deployed production ML systems before.

Inventor mindset

We don't implement the first architecture that works. We explore options, test assumptions, and design the solution that fits your specific constraints.

2-3x delivery speed

Our AI-augmented methodology compresses delivery timelines by 2-3x compared to traditional consulting.

What you'll experience

Week 1

Data access, initial training, first accuracy benchmarks, early error analysis

Week 2

Iteration on accuracy, prototype integration, demo-ready system, findings report

How this connects to our other practices

Rapid Prototyping validates ideas before full commitment. Once proven, AI-Native Workflow Design shapes the full system architecture. Agile with AI Augmentation guides how we build it in sprints.

Common questions

Have an AI idea to validate?

Start a prototype