Product design

AI-native product design.

AI-native product design is product design where AI runs through the practice: research synthesis, pattern detection, and rapid prototyping, in service of the real problem. We design enterprise workflows, design systems, and accessible interfaces, then document the decisions so they hold across leadership changes.

B2B & SaaSTravelHealthcareE-Commerce & RetailSports Tech

The problem we solve

Most enterprise software problems are not visual design problems. They are decision architecture problems. Multi-role workflows, policy-driven interfaces, and high-stakes environments where a bad interaction costs hours, not bounces.

We design for that. Our designers think like product owners, use AI across research synthesis and pattern detection, and ship every screen with a reason behind it. The decisions get documented so the next product leader does not unwind them.

What this includes

Enterprise UX

Enterprise workflows, multi-role interfaces, and user-facing experiences. AI-assisted analysis surfaces friction in the flow before users hit it.

UX research

Qualitative and quantitative research that names the trust gaps and workflow breakdowns specifically. AI compresses synthesis from weeks to days.

Prototyping

Clickable prototypes for high-stakes flows, shipped faster with AI-generated variants and pressure-tested with real users before engineering starts.

Design systems

Component libraries, token architectures, and documentation engineering actually uses. Built to scale with the platform, not against it.

Accessibility

WCAG AA+ baked in from the first wireframe. Audits, remediation, and pattern documentation so your team holds the line after we leave.

Design governance

Decisions tracked and consistency audited so the next product leader does not unwind the work. Powered by our own tool, Tenet.

Who we design for

Two kinds of teams. Enterprise platform owners, the VP Product, CPO, or engineering director at a 300 to 1500 person B2B SaaS company whose platform is three to seven years old and needs to scale, modernize, or go AI-native. And Series A and B founders rebuilding core UX, adding AI capability, or modernizing the architecture before a fundraise or a key enterprise customer.

Proof

Over a seven-year partnership we redesigned Deem's enterprise travel booking experience. Booking time fell from 425 seconds to 127, NPS climbed from 19 to 54, and the work earned 22 industry awards at WCAG AA+. For founders, we took Gritwell from zero to a production MVP in four months across web, mobile, and PWA.

Questions

Common questions about product design.

AI-native product design is product design where AI is built into the practice rather than added at the end. AI compresses research synthesis, surfaces friction in a flow before users hit it, and generates prototype variants in hours. The output is the same as good product design, a workflow that solves the real problem, reached faster and tested earlier.
UX design usually stops at the screen. AI-native product design covers the decision architecture behind the screen: multi-role workflows, policy-driven interfaces, and the trade-offs that make a high-stakes product usable. AI speeds the research and prototyping; judgment still decides what to build.
Both. We work with enterprise platform owners modernizing a product that has stopped scaling, and with Series A and B founders rebuilding core UX before a raise or a major customer. Examples include Deem on the enterprise side and Gritwell on the founder side.
A typical engagement covers research, workflow and interface design, a design system, and accessibility to WCAG AA+, with decisions documented so they hold after handoff. Project builds run 8 to 20 weeks; embedded design partnerships run longer. The first week is scoping, so the timeline is set before design begins.
AI product design

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Part of our services. See also product engineering, AI product development, and advisory.