Product & design service
Interfaces that make AI understandable and software easy to use.
We design products, internal tools, and AI experiences where people can see what the system is doing, trust what it shows them, and stay in control.
The problem
AI systems fail when people cannot understand them.
If users cannot tell what an AI did, why, or how to correct it, they stop using it. Good design is what turns a capable system into one people adopt.
What we typically hear
- Users do not trust AI output because they cannot verify it.
- Internal tools are adopted slowly because they are hard to use.
- Approval and review steps are clumsy, so people skip them.
- Inconsistent interfaces across products and features.
- Accessibility has been treated as an afterthought.
What we build
What we design
User research
Interviews and observation to understand how people actually work.
Information architecture
Navigation and structure that match users' mental models.
Interaction design
Flows for complex tasks, including review, approval, and correction.
AI experience patterns
Showing sources, confidence, state, and history so AI output can be trusted.
Visual design
Clean, consistent interfaces aligned with your brand.
Design systems
Reusable components and guidelines shared between design and engineering.
Typical use cases
Where this work pays off
AI review console
01A queue where staff approve, edit, or reject AI-prepared work quickly.
Product redesign
02Improve usability and consistency of an existing application.
Dashboard design
03Present complex data so decisions are faster.
Design system
04Create a shared component library across products.
Architecture
Design process
- 1
Research
Understand users and context.
- 2
Structure
Define flows and architecture.
- 3
Prototype
Interactive, testable designs.
- 4Human
Test
Watch real users try it.
- 5
Hand off
Specs and components for engineering.
Technology considerations
Decisions we make with you
Technology choices follow from the workflow, data, and constraints — not the other way around.
Tools
Figma for design and prototyping, with tokens shared into code.
Accessibility
Contrast, keyboard navigation, and screen reader support considered from the start.
Design-to-code
Component libraries implemented in React so design and product stay aligned.
Responsiveness
Layouts designed for every screen size the product supports.
Delivery
How the engagement runs
01
Research
Interviews, workflow observation, and analytics review.
02
Concepts
Explore directions and agree on an approach.
03
Detailed design
Screens, states, and interactions.
04
Validation
Usability testing and iteration.
05
Implementation support
Work alongside engineers through build.
Security & governance
Control is designed in, not added later.
Every system we deliver includes the controls below as a baseline. Specific compliance requirements are scoped with your team.
- Accessible contrast and keyboard support
- Clear labelling of AI-generated content
- Visible undo and correction paths
- Consent and privacy patterns in data collection flows
- Consistent confirmation for irreversible actions
FAQ
Frequently asked questions
01Do you design for products you do not build?
Yes. We can provide design only, or design and engineering together, which usually shortens the path from concept to working product.
02What makes designing for AI different?
AI output is probabilistic, so interfaces need to show sources, state, and uncertainty, and make review and correction easy. We treat those as core design problems.
03Can you work with our existing brand?
Yes. We design within your brand guidelines or help extend them into a product design system.
Related services
Often delivered together
Product
MVP & Product Development
MVP development by Neuralex Labs: product discovery, design, and engineering for AI-powered MVPs that test your idea with real users and can scale.
Engineering
Web & Application Development
Web application development by Neuralex Labs: internal tools, portals, and customer-facing apps built with Next.js, React, TypeScript, and Python.
AI
AI Copilots
Neuralex Labs builds AI copilots for internal teams and SaaS products: context-aware assistants grounded in your data, with permissions and citations built in.
Next step
Bring us the process your team is tired of doing manually.
A strategy call is a working conversation about one workflow: what it involves today, what could be automated, and what a first build would look like.
What happens next
- 1Tell us about one workflow
- 2We review it before replying
- 3A working session, then a first-build proposal