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Turning complex workflows into clear, scalable products — from discovery through delivery, brief to shipped.

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User-Centered Approach

I design solutions by deeply understanding user needs, behaviors, and pain points—then translate those insights into clear, purposeful product decisions.

AI-Native Interaction Design

I design conversational flows and AI-powered interfaces that feel intuitive, human, and genuinely useful—bridging cutting-edge AI with real-world usability.

End-to-End Design

I deliver complete product experiences from initial research and wireframes through to polished, high-fidelity prototypes ready for development handoff.

Design Systems Expertise

I build and maintain scalable Figma design systems that keep teams moving fast, aligned, and consistently on-brand across every product surface.

About

Thirty years in. Still building.

I'm Leon Govier — a Lead Product Designer and UX leader with thirty years in digital, the last decade focused on fintech, specialist lending and B2B SaaS.

1

Print & Brand

Where it started

Press-ready artwork, brand identity, the discipline of getting it right before it ships

2

Web & Development

Learning to build

HTML, CSS, Flash — designing and building in the same breath for the first time

3

UX & Interaction

Following the user

Research, wireframes, usability — design stopped being about how it looks

4

Product Leadership

Leading the room

Design systems, squads, strategy — owning outcomes not just deliverables

5

AI-Native Design

Where I am now

Claude, MCP, code-first — thirty years of judgement, modern tooling

I work contract-based across the UK, embedded with product and engineering teams at Lead, Head of Product Design, and Technical Product Manager level. I've built UX functions from zero, led design systems adopted across enterprise platforms, and shipped AI-native products solo in four weeks. The range is deliberate — I move between strategy and execution because the best design leaders do both.

My workflow has shifted. I design in Figma, prototype in code, and use Claude and MCP to take layouts directly to production React components without fidelity loss. What used to take months takes weeks. That's not a shortcut — it's thirty years of judgement applied to better tools.

The work runs through fintech and regulated environments — mortgage calculators, broker CRMs, conversational quote engines, income verification platforms, design systems spanning four audience platforms at once. Complex products with real constraints, where design decisions have commercial consequences. That's where I'm most useful.

What I design

Selected projects over the last 5 years

6 projects, one through-line — complex products shipped under real constraints. The variable is scale. Some are AI-native MVPs designed, prompted and built solo in a month — Cubik's lending platform, a reverse-matching CRM for a car dealer. Others are design systems absorbed into enterprise platforms already serving thousands — Jamf, CWT, Coincover. Fintech and specialist lending run through most of it; conversational quote engines, mortgage affordability, pricing calculators. Different domains, same job: make the complex usable.

Cubik CRM — A solo-built broker admin suite that fuses AI quoting with pipeline tracking.

Cubik CRM turns broker enquiries into pipeline-tracked deals in a single workspace. Brokers generate indicative quotes for Bridging and Commercial Buy-to-Let in under 60 seconds using an embedded AI quote engine, then track cases from enquiry to completion without switching tools. Designed, prompted, prototyped and shipped as a four-week solo build using Claude Code as the full production pipeline.

Cubik CRM — Buy to Let quote screen
Problem

Specialist lending brokers were managing cases across spreadsheets, calculators, and email — manually recalculating every quote when terms changed. Pipeline visibility was non-existent and data was lost at every handoff point between tools.

  • Quotes recalculated manually on every change
  • No pipeline visibility — cases stalled silently
  • Data lost or duplicated at every tool handoff
  • Three separate tools pretending to work together
  • No audit trail — case history impossible to reconstruct
Tools

Tool selection is part of the design decision. Claude Design extracted brand tokens; Claude Code built the React frontend directly from Figma — no screenshots, no manual handoff. AI was the production pipeline, not a helper.

  • Figma
  • Claude Design
  • Claude Code
  • React
  • Node.js
  • PostgreSQL
  • Tailwind CSS
  • Vercel
Outcome

Cubik shipped as a connected workspace in four weeks. Brokers generate indicative quotes in under 60 seconds, track cases from enquiry to completion, and review full audit trails — without switching tools or context.

  • Indicative quote generated in under 60 seconds
  • Full case lifecycle in one workspace
  • Audit trail and affordability data alongside deal stages
  • Brand to working product in four weeks solo

Anything Medical — Full-stack website and CRM built for a UK medical distributor.

Anything Medical needed to replace a single-page WordPress site with no lead capture and no product detail. I built a 20+ page marketing site with a 16-product catalogue alongside a companion CRM — capturing every enquiry, routing it to the right sales rep, and tracking deals through a 6-stage pipeline. The client went from a phone and a spreadsheet to a live sales workflow on day one.

Anything Medical — Homepage
Problem

A one-page WordPress site with no product detail and no lead capture. Enquiries were tracked manually across email and spreadsheets.

  • Single-page site, no product catalogue
  • Enquiries lost in a shared inbox
  • No sales pipeline or lead tracking
  • Sales team had no lead ownership
  • No consistent brand or design system
Tools

Built without a framework to keep the frontend fast and fully owned. Next.js powers the CRM, using serverless API routes deployed on Vercel. Claude AI accelerated the entire build.

  • Claude Code
  • HTML / CSS / JS
  • Next.js
  • Vercel
  • Resend
  • PostgreSQL
Outcome

A full marketing site and CRM shipped in four weeks. Every enquiry now lands in a pipeline with the right rep automatically assigned.

  • 20+ pages replacing a single-page site
  • 16-product catalogue across 3 categories
  • 6-stage sales pipeline with audit trail
  • Automated lead routing and email confirmation

Lookrr — Instant DVLA & MOT vehicle intelligence for UK motor trade

Lookrr gives UK motor trade professionals instant DVLA registration data, MOT history, HPI checks, and mileage fraud detection in under 2 seconds — all from a single plate search. No tab-switching, no manual cross-referencing, no missed red flags. Built as a full SaaS with tiered plans, a real-time dashboard, bulk CSV import, and a watchlist. Shipped production-ready with a complete design system, secure auth flow, and serverless API routes for live vehicle data.

Lookrr — Vehicle check dashboard
Problem

UK dealers spend 5+ minutes per vehicle manually cross-referencing DVLA, MOT, and HPI sources. No single tool surfaces fraud signals alongside verified plate data instantly.

  • Manual lookups across 3+ separate government tools
  • Mileage anomalies missed without side-by-side history
  • No bulk lookup for part-exchange appraisals
  • HPI and tax checks billed separately per query
  • No audit trail or team-shareable check history
Tools

Built in vanilla HTML, CSS, and JavaScript — no framework, no build step. Claude Code drove the full design-to-deploy loop. Vercel handles hosting and serverless API routes for live vehicle data.

  • Claude Code
  • Claude Design
  • HTML / CSS / JS
  • Vercel
  • DVLA Open API
  • Google Fonts
  • JetBrains Mono
  • Chrome DevTools
Outcome

Shipped a full SaaS platform with auth, dashboard, bulk import, and watchlist — deployed live on Vercel. Vehicle checks return full MOT, tax, and fraud data in under 2 seconds.

  • Live SaaS deployed at lookrr-project.vercel.app
  • Sub-2-second plate-to-full-report lookup
  • Bulk CSV import capped to plan allowance
  • Tiered pricing from pay-as-you-go to unlimited

Jamf ETP — Absorbing an acquired mobile threat defence platform into Jamf as sole designer.

Jamf acquired a mobile threat defence platform with a completely different visual language. I absorbed the entire product into the Jamf design system as sole designer — maintaining the operational integrity security teams depend on, redesigning threat detection and incident response workflows, and contributing eight new component patterns back into the core system used across all Jamf products.

Jamf ETP — Security console
Problem

Jamf acquired a mobile threat defence platform with a completely different visual language and interaction model. Security operations teams using both products were context-switching between two distinct UIs — adding cognitive load at exactly the point where speed and accuracy matter most.

  • Acquired product had entirely separate component patterns
  • Different interaction models across Jamf and ETP
  • Security teams context-switching between two distinct UIs
  • Operational integrity requirements blocked a simple reskin
  • No existing Jamf patterns for security-specific functionality
Tools

Embedded as sole designer for 8 months, working directly with the Jamf design system team and the ETP security product team to validate workflows against real threat scenarios.

  • Figma
  • Jamf Design System
  • React
Outcome

ETP security console fully integrated into the Jamf design system. Security teams move between products without context-switching. Eight new component patterns contributed back to the core Jamf system, now used across other Jamf products.

  • 1 designer across the entire product
  • 100% Jamf design system compliance
  • 8 new patterns contributed to core system
  • Phased delivery — no security workflow disrupted

Coincover — A tokenised design system built from zero across four audience platforms in four months.

Coincover had four products, four visual languages, and zero shared infrastructure. I built a fully tokenised design system from zero — one component library spanning customer, partner, admin, and operations platforms — in four months. Brand updates that previously required four separate efforts now propagate across all products in minutes. The in-house team was self-sufficient within two weeks of handover.

Coincover — Design system
Problem

Four separate products, four separate visual languages, zero shared infrastructure. Every brand decision had to be implemented four times. The design team was maintaining four Figma files with no shared styles — a single update required four separate design and development efforts.

  • Four products with one brand but no shared foundation
  • Components duplicated with inconsistent variations
  • Four separate Figma files, no shared styles or tokens
  • Brand updates required four separate implementation efforts
  • Cost of inconsistency compounding with every sprint
Tools

Embedded for 4 months, building the token architecture, component library, and Storybook documentation in parallel — then running a structured handover programme to make the in-house team self-sufficient.

  • Figma
  • Design Tokens
  • React
  • Storybook
Outcome

Production design system adopted across all four platforms from one component library. In-house team self-sufficient within two weeks of handover — extending the system independently from month one.

  • 4 audience platforms served from one system
  • Zero to production in 4 months
  • Brand updates: weeks → minutes
  • Team shipping new components without involvement

AdaptiveCRM — An AI-native CRM that reverse-matches found cars to the customers who want them.

AdaptiveCRM reverses the usual workflow: instead of searching stock for customers, it searches customers for stock. A luxury-car dealer drops in a screenshot, photo, or WhatsApp message of a vehicle and AdaptiveCRM extracts the details, then ranks which customers in the database actually want it — in under ten seconds. Designed and prototyped for a UK luxury-car dealer exploring AI-native sales tools.

AdaptiveCRM — Customer match results
Problem

Luxury-car dealers find exceptional vehicles at auction but have no fast way to identify which customers would want them. The workflow relies on memory, manual CRM browsing, or blanket emails — slow, imprecise, and damaging to the client relationships luxury dealers depend on.

  • No way to query the CRM with a found vehicle as the starting point
  • Dealers relied on memory or blanket outreach
  • Found cars became missed opportunities
  • Generic outreach undermined high-touch client relationships
  • Customer preference data existed but was never activated
Tools

Solo build over 3 weeks. Claude API drives vehicle detail extraction from unstructured input and customer match scoring. Claude Code built the React frontend via MCP. Validated with a UK luxury-car dealer using real auction listings and their actual customer database.

  • Figma
  • Claude Design
  • Claude Code
  • Claude API
  • React
Outcome

Working prototype validated with a UK luxury-car dealer. Match scoring surfaced the right customers for the right cars. Transparent scoring breakdowns let dealers personalise outreach based on the specific match reasons — not just a ranked list.

  • Sub-10-second match generation
  • Zero manual stock entry required
  • Full match score transparency per customer
  • Prototype ready for production build
Interested in working together? I'm available for contract engagements now.

Built for you

What I build

Production-ready digital products designed and shipped end-to-end — from AI-native tools and design systems through to calculators, CRMs and compliance workflows.

Calculators & Quote Engines

Complex financial calculators and AI-powered quote tools that turn broker enquiries into structured outputs in seconds. Built for specialist lending, mortgage and fintech environments where accuracy and speed both matter.

  • Mortgage and bridging loan calculators
  • AI conversational quote engines
  • Affordability and DTI threshold tools
  • Rate comparison and scenario modelling
CRM & Pipeline Tools

Broker and sales CRMs that connect quoting, pipeline tracking and case management in one workspace. Designed for teams running their business across too many disconnected tools and losing data at every handoff.

  • Broker admin and deal pipeline suites
  • AI reverse-matching and stock tools
  • Case tracking from enquiry to completion
  • Audit trails and commission calculators
Design Systems

Token-driven component libraries built from zero and adopted across platforms. One source of truth flowing from Figma through MCP to production code — with governance and documentation that lets teams extend them independently.

  • Multi-platform token architecture
  • Component libraries with usage guidelines
  • Figma to code via MCP and Claude
  • Handover programmes for in-house teams
AI-Native Products

Conversational interfaces, agent-based workflows and human-in-the-loop tools built for regulated environments. Designed where the AI is a first-class part of the experience — not a feature bolted on after the fact.

  • Conversational UX and chat interfaces
  • LLM-powered data extraction and matching
  • Human-in-the-loop compliance workflows
  • AI-assisted onboarding and guided flows
SaaS Dashboards & Analytics

Internal and customer-facing dashboards across complex data domains — built with accessible visualisation systems that non-specialist teams can extend. Five domains shipped from one analytics design system at CWT.

  • KPI and performance dashboards
  • Multi-domain analytics design systems
  • Accessible data visualisation components
  • Role-based views and reporting tools
Compliance & Verification Platforms

Guided digital workflows that replace paper-based processes in regulated environments. Built for mortgage income verification, educational compliance and healthcare — where mandatory validation and audit trails are non-negotiable.

  • Income verification and affordability flows
  • Document upload and OCR validation
  • Multi-step guided compliance workflows
  • Approval routing and audit trail reporting
Currently available for contract. Tell me what you're working on.

Process

How we'll work together.

Good product design happens between people, not in isolation. I embed in teams, work through ambiguity alongside engineers and stakeholders, and keep the process visible at every stage — no black boxes, no surprises at handoff. Here's how that typically looks from first conversation to something live in the wild. AI accelerates the parts that should be fast — never the parts that require judgment.

1

01 / Discover

Understand the problem space

Sit with the team and the users. Map constraints, workflows, the messy reality — not the polished version. The real signal lives in the conversations, not the brief. AI helps synthesise interview transcripts and surface patterns across sessions faster — but the judgment about what actually matters still happens in the room.

2

02 / Define

Frame the right problem, not symptoms

Synthesise what research actually says, not what everyone assumed it would. AI helps stress-test assumptions and spot contradictions in the data before they become design debt. Kill scope that doesn't serve the core job. Alignment here — whether it takes a week or three — saves months later.

3

03 / Develop

Figma to production

Design in Figma — components, tokens, layouts, flows. Claude Design extracts brand tokens; Claude Code builds working components directly from layouts, removing the manual translation step entirely. Multiple review cycles still happen — AI accelerates the gap between prototype and production, it doesn't skip it.

4

04 / Deliver

Polish, test, and launch

Pair with engineers through QA, polish the details, then watch it in the wild. AI helps catch edge cases and generate test scenarios faster — flagging regressions and surfacing what manual review tends to miss — but the final call on what ships is always a human one. Shipping well means staying close until it's truly done.

Looking for a design lead who ships? Let's talk about your team and your product.

Skills

What I bring to the table

Thirty years in digital, the last decade focused on product design leadership across fintech, SaaS and regulated environments — from discovery and research through to shipped, production-ready products.

Leadership & People

How I build and lead design teams — establishing the culture, process and operating model that lets designers do their best work.

Experience

  • 20+ years leading product design
  • 3 UX functions built from zero
  • C-suite design advocacy
  • Enterprise and startup environments
  • Contract and embedded leadership

Approach

  • Design direction and quality ownership
  • Hiring and capability building
  • Mentoring senior and mid-level designers
  • Design ops and process improvement
  • Embedding design across non-design teams
Strategy & Product

How I connect design decisions to business outcomes — from shaping roadmaps and defining success through to facilitating discovery and keeping scope honest.

  • Outcome-focused roadmap thinking
  • Jobs-to-be-done and problem framing
  • Research synthesis and insight to action
  • OKR alignment and success metrics
  • Design maturity assessment
  • Discovery facilitation and workshops
  • Requirements definition and prioritisation
  • MVP scoping and phased delivery
  • Commercially aware decision making
  • Design advocacy at leadership level
Domain Expertise

The sectors and product types I know deeply enough that domain expertise replaces research time — I understand the constraints before the brief lands.

  • Fintech and specialist lending
  • B2B SaaS and regulated platforms
  • Mortgage and affordability platforms
  • CRM and pipeline tooling
  • Enterprise design systems at scale
  • AI-native and conversational UX
  • Analytics and data visualisation
  • Security and threat management
  • Healthcare and compliance-led environments
  • Multi-tenant SaaS and white-label products
Design Delivery

How I close the gap between what's designed and what ships — using AI-assisted pipelines that take Figma layouts to production components without fidelity loss.

Qualifications

  • PMI Project Management
  • PMI Agile Foundation / Practitioner
  • PMI Product Owner
  • PMI Product Manager
  • SAFe Agile Certification

Process

  • Figma to React via Claude MCP
  • Component generation with Claude Code
  • Claude Design for brand token extraction
  • Figma layouts to production without fidelity loss
  • One source of truth from Figma to shipped
Delivery Practice

How I work inside product and engineering teams — from sprint planning and backlog refinement through to stakeholder reviews and regulated release cycles.

  • Sprint planning and backlog refinement
  • Cross-functional squad working
  • Agile and SAFe delivery frameworks
  • Azure DevOps · Jira · Linear
  • Stakeholder reviews and demo facilitation
  • Requirements definition and scoping
  • Acceptance criteria and story writing
  • Design within regulated release cycles
  • Risk and dependency management
  • Continuous delivery and deployment
Tools & Infrastructure

The full stack I use to design, build and ship — from component libraries and design systems through to deployment pipelines and production environments.

  • GitHub · Vercel · Netlify
  • Notion · Confluence
  • Figma · Storybook
  • Claude Code · Cursor
  • PostgreSQL · Node.js
  • React · Next.js · TypeScript
  • Tailwind CSS · shadcn/ui
  • Azure DevOps pipelines
  • CI/CD and production deployment
  • Environment management across staging and live
Design

From early wireframes to polished, production-ready components. The tools I use to design, prototype and build at every fidelity.

  • Figma
  • Claude Design
  • Figma AI
  • Figma Make
  • Adobe Creative Suite
  • React
  • Vite
  • Next.js
  • Tailwind CSS
  • Claude Code
  • Cursor
  • v0 (Vercel)
Product Design & Design Systems

Product design leadership across fintech, SaaS and regulated environments — from discovery through to shipped.

  • Interaction design for complex workflows
  • Journey mapping and experience design
  • Information architecture
  • Service flow and experience mapping
  • Design systems and component libraries
  • Design system governance
  • Cross-platform product design
  • Web, SaaS and mobile product experience
AI-Enabled Product Design

Designing AI-enabled products where the model is a first-class part of the experience.

  • Conversational UX design
  • Agent-based interaction models
  • Human-in-the-loop design
  • AI in regulated environments
  • AI-assisted discovery workflows
  • AI-assisted design and delivery
  • LLM capabilities in product experiences
  • AI-native interface patterns
Day rate, fixed scope or retainer. Get in touch and I'll send a proposal.

Feedback received

Twelve years. Twelve voices.

Recommendations gathered over the years from the people on the other side of the work — chief officers, product directors, design leads and engineers. Different companies, different briefs, but the themes recur: clarity under pressure, design that holds up after launch, and someone equally at home in a stakeholder room or deep in the detail. Their words, not mine.

FAQs

Some important questions

You might have questions about working with me. If what you need isn't answered here, please reach out directly.

I work on product design, design systems, AI-native experiences and cross-functional delivery — usually embedded with product and engineering teams in fintech, SaaS or regulated environments. I take on leadership roles (Head of Product, UX Lead), senior IC positions, and delivery consulting where design maturity or velocity needs improvement. I don't do branding, marketing sites, or one-off logo work.

I embed as part of the team — either leading design direction or working hands-on as a senior IC. I work contract-based (day rate or fixed scope), on retainer for ongoing support, or fractionally for smaller teams that need consistent design leadership without a full-time hire. I'm comfortable in Agile, SAFe, or custom delivery models.

I work hybrid. I'm based in Cardiff with regular availability in London, and I'm set up for effective remote collaboration across distributed teams. I'm flexible for on-site days, sprint planning, workshops or stakeholder sessions when face-to-face adds value. Most of my work happens remotely with intentional in-person touchpoints.

I follow Double Diamond — Discover, Define, Develop, Deliver. What changes project-to-project is phase weighting and tooling. I use Figma for design, Claude and MCP for AI-assisted delivery, and work directly with engineers to ship production-ready components. Discovery and research stay human-paced; design-to-code is where AI compounds velocity.

Yes. I have strong front-end fluency (HTML, CSS, JavaScript, React) and use AI-assisted workflows to go from Figma to production code. I'm not replacing engineers — I'm accelerating handoff quality and reducing translation loss. I can prototype, build design systems, or ship MVPs when speed matters.

Extensively. I design AI-native products (conversational UX, human-in-the-loop workflows, LLM-assisted experiences) and use AI in my delivery process (Claude, MCP, automated testing). I'm particularly experienced in regulated environments where AI needs guardrails, transparency and human oversight.

Fintech, lending, SaaS, healthcare and regulated platforms. I understand compliance constraints, complex workflows and high-stakes user journeys. I've designed mortgage platforms, trading tools, CRM systems, analytics dashboards and AI-enabled lending products. If your domain is complex and regulated, I've likely worked in something similar.

It depends on scope. Short-term contracts run 4–12 weeks (design system setup, product redesign, discovery sprint). Longer engagements are 3–6 months (Head of Product, embedded design lead). Retainers are ongoing. I'm flexible and scope work to match your delivery cadence and budget.

Day rates vary based on scope, duration and engagement type. I'm transparent about pricing and structure proposals around outcomes, not hours. For fixed-scope work, I provide a clear estimate upfront. For ongoing work, we agree on a retainer or day rate. Get in touch and I'll send a proposal.

Both. I build scalable design systems (components, tokens, documentation, governance) aligned to your tech stack — whether that's React, Angular, Salesforce LWC, or custom. I also lead end-to-end product design from research through delivery. Often both happen together: designing the product while establishing the system to scale it.

Yes. I've led UX transformation in fintech and SaaS orgs — introducing research practices, design ops, better tooling and cross-functional workflows. I mentor designers, upskill teams on Figma, Storybook and delivery processes, and help product and engineering teams raise design quality without slowing down.

Let's talk. I start most engagements with a discovery conversation — understanding your product, team structure, delivery challenges and goals. From there, I'll recommend the right scope: whether that's hands-on IC work, design leadership, systems thinking, or process improvement. No obligation, just clarity.

Still have questions? I'm happy to jump on a call — no obligation, just a conversation.