Services
Shape, Build, Accelerate, Scale.
Four service areas. Shape defines what to build. Build designs it and validates it with users. Accelerate brings AI into your product process without compromising quality or control. Scale builds the design team that sustains it.
01 · Strategy and research
Shape
For teams deciding what to build, or working out why a product isn't performing.
Vision and innovation workshops
Align leadership on a product vision, and translate it into a prioritized roadmap.
Design research
User interviews, field studies, usability testing and journey mapping.
User personas and needs
Who your users are, what they are trying to achieve, and where the current product falls short.
UX audits and design reviews
An expert evaluation of an existing product, with prioritized, actionable recommendations.
Information architecture
Structure, navigation and content models for complex products.
Solution architecture
How user flows, data, systems and integrations fit together, defined before development begins.
Customer, employee and service experience
End-to-end journeys, designed across channels, teams and systems.
02 · Design and AI prototyping
Build
For teams that need something tangible to test or launch.
Idea to working prototype
An interactive, AI-built prototype in days, tested with real users.
Product and app design
Web and mobile applications, from user flows to polished interface design.
End-to-end builds
Design and development of a first release (MVP), using AI-assisted engineering.
Design systems
Components, design tokens and guidelines that keep products consistent and faster to build.
03 · AI in your product process
Accelerate
For teams adopting AI in product development who want speed without losing quality or control.
AI process mapping
Identify where AI can accelerate your team's work, and where it should not be used.
A Design Constitution for your brand
We write a
design-constitution.mdfor your product, covering your design system, interaction patterns, brand rules, and accessibility and compliance requirements. Every AI tool your team uses reads it, so output stays on-brand from the first draft, whichever model generates it.Spec-driven development
Requirements, design and task specifications are reviewed and approved before any code is written, so AI builds exactly what was agreed.
Skills for your team's practices
Your design and engineering standards, written as reusable AI skills, so agents apply them consistently and your team stops repeating the same corrections.
Maker and checker loops
One agent builds. A separate agent verifies the work against agreed quality gates and records the evidence. A task is complete only once it has been verified.
Security built in, even when AI writes the code
Approved dependencies only, secrets kept out of prompts, a security review on every change, automated checks in your CI pipeline, and code prepared for penetration testing.
Security review for AI-built apps
For founders who built an application quickly with AI. We assess it for common risks, including weak authentication, exposed secrets, vulnerable dependencies and data leaks, fix what we find, and prepare it for professional penetration testing.
AI training for your teams
Hands-on training for designers, engineers, product managers and other staff in Claude, Figma MCP, AI prototyping and the safe use of AI in daily work.
04 · Teams and leadership
Scale
For organizations building or growing a design function.
Fractional Head of Design
Senior design leadership a few days a week, until you are ready to hire full time.
Design organization setup
Roles, processes, rituals, tooling and culture for an effective design team.
Hiring designers and researchers
Role definitions, portfolio screening, interview loops and assessments, to find people with the right mindset for AI-enabled teams.
Mentoring and coaching
One-to-one guidance for designers and design managers.
Embedded designers
Vinrax designers, hired and managed by us, working as part of your team.
Engagement models
Choose the engagement that fits.
Typical durations. We agree the scope and timeline with you before work begins.
| Model | Best for | Typical length |
|---|---|---|
| UX audit | A clear, prioritized view of what to fix | 1 to 2 weeks |
| Prototype sprint | Testing an idea with users before building it | 2 to 3 weeks |
| Build | Designing and launching a first release | 6 to 12 weeks |
| AI process setup | Design Constitution, specifications, skills and quality checks in your team's workflow | 4 to 6 weeks |
| AI training | Hands-on workshops for your teams | 1 to 3 days |
| Security review | Assessing and fixing an AI-built application | 1 to 2 weeks |
| Retainer | Ongoing design and research support | Monthly |
| Fractional leadership | Design leadership ahead of a full-time hire | Monthly |
| Embedded designers | Additional design capacity within your team | Monthly |
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