Services
Design, build, and ship production software.
Five services built around what actually ships. Outcome-based engagements available for teams with a clear KPI.
Most enterprise software problems are not visual design problems. They are decision architecture problems. Multi-role workflows. Policy-driven interfaces. 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. Decisions get documented so the next CPO doesn't unwind them.
UI/UX Design
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, pressure-tested in front of 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.
Accessibility as a differentiator. Most teams treat accessibility as a checklist at the end of a project. We build it in from the first wireframe. WCAG 2.1 AA+ compliance, inclusive UX patterns, and remediation audits when needed. For platforms serving enterprise clients, accessibility is a procurement gate, not an afterthought.
Full-stack engineering across React, React Native, Flutter, Node, Python, and cloud-native infrastructure. Built for teams that can't afford the handoff tax that kills most enterprise releases. AI is part of the architecture from the start: code generation, automated testing with AURA, and intelligent backend orchestration that reduces manual handoffs.
Front-End Development
Fast, accessible, responsive interfaces in React, React Native, Flutter. AI-assisted review catches regressions before QA does.
Full-Stack Engineering
APIs, backend systems, databases, and cloud infrastructure built for uptime and scale. Telemetry and anomaly detection from day one.
Prototype to Production
Take a Cursor, Lovable, Replit, v0, or Bolt prototype and harden it to production: test coverage, error handling, security, deploy pipelines, telemetry.
Mobile Applications
Native and cross-platform apps that feel like consumer software and hold up under enterprise constraints.
Release Confidence
Every release validated with AURA. Intent-driven testing across API, UI, and data layers. Not brittle scripts, not manual checklists.
We build products where AI is the product, not a demo tab. Agent interfaces that operate inside real workflows, computer vision systems trained on actual domain data, and release confidence designed in from the start: evals, fallbacks, telemetry. Not retrofitted after incidents.
Agent Interfaces
Agents that operate inside real workflows, not demo chatboxes. Support agents, internal tools, embedded copilots with hand-off boundaries you can audit.
Computer Vision
Visual recognition and quality inspection trained on your domain data. Built for production floor, warehouse, clinical, and field environments.
AI-Driven Workflows
Backend flows and system-level triggers that remove manual handoffs. Scoped to the workflow, not the feature list.
Model Integration
LLMs, custom models, and third-party AI APIs integrated with evals, fallbacks, and telemetry designed in from the start.
We pick the workflow that's costing the business the most (customer ops, sales, internal tooling) and embed AI where it reduces friction. Then we train your team to run it and measure outcomes against specific targets. For teams with a clear KPI and the authority to act on it, we structure the engagement around the outcome, not the hours.
Workflow Baseline
We map the target workflow, benchmark the current KPI (time, cost, conversion, ticket rate), and set the outcome target the engagement is measured against.
AI Implementation
Build the integration end-to-end: data pipelines, model selection, API connections, UI changes, and rollback paths. Merged into your stack, not staged forever.
Capability Transfer
Your team learns to run and evolve the system while we are still in the room. No dependency on us long-term. That is the point.
Outcome Measurement
KPI tracked against the baseline. If the number is not moving, we say so and adjust. For outcome-based engagements, payment is tied to the KPI moving.
Most engineering teams can't move to AI-native development on their own. Not because they lack skill, but because they lack the scaffolding. We pair with your engineers on real code, install Claude Code and Cursor workflows, write AGENT.md files, set up evals and CI, and leave your team shipping faster than when we arrived. Not a deck. Not an 80-slide plan. Code, process, and transferred capability. For teams that want to pressure-test an idea first, we also run short-form audits (product, workflow, or AI readiness) with a practical plan at the end.
AI-Native Pairing
We pair senior engineers and designers with your team on real code. Claude Code and Cursor workflows installed, AGENT.md written, evals and CI set up. Your team ships faster before we leave, not just after training.
Audits with a Plan
Short-form audits when you need to pressure-test a direction: product, design system, architecture, or AI readiness. Output is a practical plan with priorities and tradeoffs, not an 80-slide deck.
Test coverage in a day
AI-generated test suites that cover your existing codebase, giving you a safety net before any changes.
Reduced dependencies
Identify and remove unnecessary libraries, shrink your supply chain risk, and simplify maintenance.
Designer+AI workflows
Bridge the gap between design and code with AI-assisted handoffs that keep both sides in sync.
Structured modernization
Not a rewrite. A phased, risk-managed path from legacy patterns to AI-native development practices.
Engagement
Ways to work with us.
Every engagement is structured around your outcomes, not our billing model. All four models run on CRISP, our intent-driven delivery framework. Typical engagement sizes are listed with each model.
Embedded teams
Senior designers and engineers join your team and ship inside your repo. You manage the work. We stay long enough to carry context. Typical engagement: 3 to 12 months.
Starting around $25K per month
Project builds
You hand us the problem. We own the design, build, and delivery end to end. Fixed scope, fixed timeline, CRISP playbook. Typical engagement: 8 to 20 weeks.
Starting around $75K. Most projects land between $100K and $400K
Venture partnership
We co-build with founders who want a technical partner, not just a vendor. Aligned incentives, shared commitment, and equity-adjacent terms where the shape of the work makes sense. Typical engagement: one quarter minimum.
Mixed cash and equity. Terms negotiated case by case
Advisory
Not ready for a build. We audit your product, workflows, or AI readiness and hand back a practical plan with priorities and tradeoffs. Typical engagement: 1 to 4 weeks.
Fixed fee, $10K to $40K depending on scope
Tell us the problem. We'll tell you the approach.
No pitch deck. No sales process. A conversation about what you're building and how we'd approach it.
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