Skip to content
Engineering

Design systems and UI/UX design

One coherent product, designed once, built everywhere.

Component libraries, design tokens, and user experience research that scales across products.

tokens / componentsv3.2
brandinkmistokwarnerr
AaAaAaAaDisplay · H2 · Body · Caption
PrimaryHoverFocusDisabled
space scale
WCAG 2.1 AAStorybookRadix
Illustrative interface
Category
Engineering
Deliverables
04 core
Core stack
Figma Design Systems · Tailwind CSS · Storybook
Typical first phase
Audit
The brief

Scalable UI/UX Design Systems & Accessibility First Frontend

We design systems, not just screens. Tokenized component libraries, real user research, and accessibility built in from the first prototype keep your product coherent and fast to build on as it grows.

Without it
  • Every screen has a slightly different button, spacing and colour.
  • Designers and developers keep rebuilding the same components.
  • Accessibility issues surface after launch, or in a complaint.
With Caudify
  • A tokenised system shared by design and code.
  • Faster feature delivery from reusable, documented components.
  • Accessibility built into every component, not bolted on.
01

Design system architecture

Tokens, foundations and governance that let the system scale across products and themes.

Capabilities
  1. 1Design tokens (colour, type, space)
  2. 2Theming & dark mode
  3. 3Contribution & versioning
02

Component library (Storybook)

Production components in code, documented and tested in Storybook.

Capabilities
  1. 1Accessible primitives (Radix)
  2. 2Visual regression tests
  3. 3Usage documentation
03

User research & testing

Evidence from real users that shapes flows before they’re built.

Capabilities
  1. 1Interviews & usability tests
  2. 2Journey & task mapping
  3. 3Prototype validation
04

Accessibility audits (WCAG 2.1 AA)

An audit against WCAG 2.1 AA with prioritised, developer ready fixes.

Capabilities
  1. 1Automated & manual testing
  2. 2Screen reader walkthroughs
  3. 3Remediation plan
How we deliver

AI is in the room from day one.

We don't bolt AI on at the end of a project. It's part of how we research, design, build, test and document every engagement, which is how a small senior team moves quickly without cutting corners. A person reviews everything the models produce.

On design system

AI audits your existing interface for inconsistencies and drafts component documentation; our designers define the system itself.

  • A person signs off. No model output reaches your users or your codebase without review.
  • Your data stays yours. Zero-retention API settings or private models when your data requires it.
  • Model-agnostic. We pick models by measured quality, cost and privacy, not by vendor.
  1. Discover

    Requirements mapped with LLMs

    With your permission, briefs, tickets, call notes and analytics exports go into a private workspace. LLMs map requirements, edge cases and open questions, so nothing said in a workshop gets lost. People run the workshops; the model keeps the record.

  2. Prototype

    Something real to react to, early

    First-pass screens, flows and copy variants are generated from the spec, then shaped by our designers. Decisions happen on a clickable prototype instead of a document, and the final design system stays human-made.

  3. Build

    AI pair programming, human review

    Engineers work with AI coding assistants for scaffolding, tests and refactors. Every change is read by a person and scanned by Caudilysis, our own static analysis platform, before it merges.

  4. Verify

    Evals and generated tests in CI

    AI features get an evaluation set built from real examples, and every model or prompt change is scored against it. Everything else gets generated test cases that an engineer reviews and keeps in the pipeline.

  5. Ship and learn

    Docs, runbooks and monitoring

    Documentation, runbooks and release notes are drafted with AI and checked by the team. After launch, monitoring and usage data feed straight into the next iteration.

Engagement

How a design system engagement runs.

The indicative shape of a first engagement. Phases overlap on purpose, so we start building while discovery is still sharpening the plan.

  1. 01AuditInventory UI, research users, find gaps.
    2 wks
  2. 02FoundationsTokens, type, colour, spacing.
    2 wks
  3. 03ComponentsBuild, document, test in Storybook.
    6 wks
  4. 04AdoptionMigrate screens, enable teams.
    3 wks

This is indicative only. Every engagement is scoped with you before it starts.

Fit

Is design system right for you?

  1. 01

    You run more than one product, platform or brand.

  2. 02

    Your UI has drifted, and it slows every release.

  3. 03

    Accessibility is a requirement, not a nice to have.

Not sure it fits? A free assessment will tell you

caudify / services / design_systems.yml
# Service manifest
service:    Design Systems & UI/UX
category:   Engineering
deliverables:
  • Design system architecture
  • Component library (Storybook)
  • User research & testing
  • Accessibility audits (WCAG 2.1 AA)
stack:
  • Figma Design Systems
  • Tailwind CSS
  • Storybook
  • Radix Primitives
  • Design Tokens
  • WCAG Accessibility
phases: 4
next_step:  free assessment
Questions

Design system questions, answered.

Do we need a full design system?

Not always. Smaller teams often need only tokens and a core component set. We size the system to your product and team so it speeds you up rather than adding ceremony.

Which tools do you use?

Figma for design, tokens synced to code, Tailwind CSS or CSS variables for styling, Radix primitives for accessible behaviour, and Storybook for documentation and testing.

Will it work with our existing codebase?

Yes. We plan a gradual migration, replacing components screen by screen, so there is never a big bang rewrite.

Start with a free assessment.

Tell us what you're building, improving or automating. We'll come back with an honest view of where design system fits and the fastest path to production.

Next serviceEngineeringProduct as a Service