AI transformation
AI Design Agency
We help product teams design AI-enabled experiences that feel intuitive to users, and build the design infrastructure to support AI features without creating interface chaos.
Credentials
Credentials
2020 Red Dot Design Award
MIT Design LabUp Strategy Lab helps B2B tech companies design AI features that users actually understand and adopt, and build the design systems that make those features scalable rather than one-off experiments.
Over 12 years and 100+ digital products designed. Red Dot Award winners. Design experience rooted in MIT methodology.
Why AI features get ignored
Adding AI to your product is straightforward. Designing it so users trust and use it is not.
Most teams shipping AI features are engineering-led by necessity. The model works. The output is good. But the interface around it, how users invoke it, understand what it's doing, review its output, and recover when it's wrong, is an afterthought. The result is AI functionality that users either ignore or distrust. The design layer is what separates an AI feature from an AI-powered product.
Design around the model
AI features are only as good as the design that surrounds them.
Up Strategy Lab helps you close the gap between what your AI can do and what your users will actually use. Book a call to talk through what you're building and where the design challenges are.
What the work looks like.
Work in this area.
Viking Analytics
Brand, website, partner program and product redesign for an AI predictive maintenance platform.
Outcome: 100% more website traffic
CapillaryFlow
A full business transformation, spanning rebranding, website, partner program, digital product, and go-to-market strategy, that turned a single-product golf company into a multi-vertical technology
Outcome: Red Dot Award
MuchSkills
We built MuchSkills ourselves, from a colour-coded spreadsheet to a Red Dot Award-winning skills intelligence platform now used by teams worldwide.
Frequently asked questions
What does AI-enabled design actually mean in practice?
It means two things: designing product interfaces that incorporate AI features in ways users can understand and trust, and using AI tools within the design process itself to accelerate research, iteration, and production. We do both.
Do you need to understand our AI model to design the interface around it?
We don't need to understand the model architecture, but we do need to understand the AI's capabilities, its failure modes, and the decisions it makes so we can design appropriate feedback, control, and transparency mechanisms into the interface.
Is AI design only relevant for AI-native companies?
No, it's increasingly relevant for any B2B SaaS product adding AI features to an existing product. The design challenge of retrofitting AI into an established interface is often harder than building AI-native from scratch.
How quickly can AI design workflows be introduced to a product team?
For design workflow automation, most teams see meaningful efficiency gains within the first two to four weeks. For product-facing AI feature design, the timeline depends on the complexity of the feature and the current state of the design system.
Book a call.
If you're shipping AI features and struggling with how to design interfaces users will trust, let's talk about the specific challenges you're facing.
Book a meeting