We design the screens, write the software, and keep it running when traffic, data, and models grow.
Interface
16ms
Intelligence
p95
Infrastructure
99.9%
The stack we own
AI-first does not mean model-only. We ship the screens, the intelligence, and the infrastructure as one product.
Frontend
16ms
target frame
Design systems, motion, and performance budgets. We build the surface, then keep it fast as the product grows.
Backend
p99
latency owned
APIs, data models, and AI pipelines designed for change. Auth, payments, and domain logic that still make sense at 10x traffic.
Scale
99.9%
uptime posture
Cloud, CI/CD, and observability so growth is a config change, not a rewrite. We plan for load, failure, and the next ten markets.
Services
Full-stack product work, with AI in the architecture rather than tacked on later.
How we scale
We do not hand over a demo. We hand over a path: traffic in, intelligence in the middle, data and ops that survive launch week and year three.
01
02
03
04
Designed for load · instrumented for failure · ready for models in production
In-house
People, pipeline, projects, campus, and books. Five products we design, run, and scale ourselves.
Selected work
Client work in education, health, HR, events, and automation. AI only where it earns its keep.
Working process
01
We start with the problem: what has to work on day one, where AI actually helps, and what can wait. You leave with a plan, not a pitch.
02
Working software every week, not a big reveal at the end. Interface, backend, and models move together so you can click the real thing.
03
We test the product and the model. After launch we stay on for load, fixes, and the next release.
Proof
Six years of shipping. Five in-house platforms. Thirteen client products in the field. We measure screening time, engagement, and whether the system stays up.
“We came in with a messy brief and left with something our users actually use. They did not disappear after launch either.”
“Honest about timelines, picky about the unglamorous backend work, and they treated the UI with the same care. That combination is rarer than it should be.”
“We needed an AI feature that would survive production, not a demo. They put evals in the build and we still ship on that system today.”
FAQ
A short call to understand the problem, the constraints, and whether we are a fit. If we are, we send a written scope: what we will build, what we will not, and a timeline. No 40-page deck.
Let’s work together
A short note is enough. We will come back with how we would build it, and whether we are the right team.
