Production AI, engineered end to end, six eval-gated service lines.
The same playbook, tuned to the constraints of the sectors we ship into most.
Proof, not promises, selected case studies and recognition.
A transparent, 3-phase playbook from first audit to embedded team.
The senior team behind the work, and how to reach us.
A capable model that users do not trust gets abandoned. We design the human side of AI (conversational UX, confidence and steering controls, graceful failure) so your AI is adopted on the second click instead of churned on the first.
Good AI engineering is invisible to users. What they see and feel is the design. We bridge the gap between model capability and product experience.
Information architecture and interaction design for chat interfaces, voice agents, and AI copilots. We design the conversation flow, not just the UI.
System prompt engineering, few-shot example curation, and prompt versioning as a first-class product artefact not an afterthought buried in code.
Figma-to-code design systems built for AI-native products. Loading states, streaming text, confidence indicators, and graceful fallbacks designed from the start.
Feedback mechanisms, correction flows, and escalation paths that let users train your AI through normal usage improving accuracy over time.
Voice, image, and document input alongside text. We design and build multi-modal AI experiences across web, mobile, and native desktop.
WCAG 2.1 AA compliance, screen-reader-friendly AI output, RTL support, and i18n for the markets you actually serve.
Users don't trust AI by default. Trust is built through transparency, accurate uncertainty communication, and consistent behaviour over time.
The words your users type and the words your system sends to the model are product decisions, not engineering ones. We design them with the same rigour as UI.
AI fails 10% of the time. The interface must handle failure gracefully, offer a correction path, and never leave the user confused about what happened.
Streaming responses feel responsive even at high latency. We design loading states, typing indicators, and progressive disclosure for all AI output.
AI outputs are probabilistic and variable. Regular UX designs for deterministic states. AI-first design accounts for streaming responses, uncertainty indicators, correction flows, and graceful degradation when the model is wrong.
Yes. Prompt engineering is a design discipline, not an engineering one. We design the full user journey from natural language input through AI processing to final output display.
Absolutely. We extend existing Figma design systems with AI-specific components and interaction patterns. If you don't have a design system yet, we build one.
Yes. AI features need user testing more than most, because user mental models of AI are often wrong. We run moderated sessions to find where users get confused or lose trust.
30 minutes, one of our seniors, no slide deck. By the end of the call you'll know whether we're the right team, and if not, who is.