// WHAT WE DO

Four things, done properly.

We're not a generic dev shop. We build production AI and the products around it — named tools, real outcomes, no demoware.

[ 01 — AGENTS ]

AI agents & automation

Multi-agent systems that research, act, and review on a loop — built to run unattended, log every decision, and improve against their own track record.

→Manual workflows that don't scale and drift over time
→Decisions that need to be repeatable and auditable
→Teams that need to do more without hiring more
e.g.  AlphaLoop — a research/execute/review trading loop that runs every day.
01agent.research()
02agent.execute()
03agent.review()
↑ closed feedback loop
query → retrieve 12 chunks
grounded answer + citations
tokens + latency + cost logged
[ 02 — INTEGRATION ]

AI integration · RAG & LLM

RAG and LLM pipelines wired into your data and tools — grounded in your sources, observable end to end, and cost-aware by design.

→LLM answers that hallucinate or can't cite a source
→Knowledge locked in docs, tickets, and databases
→Spiralling token bills with no visibility
e.g.  An assistant that answers from 10k internal docs with citations.
[ 03 — PRODUCT ]

Full-stack product engineering

Web and mobile products from zero to production on a TypeScript + Supabase stack — the same stack we ship our own products on.

→An idea or prototype that needs to become a real product
→AI features that need a solid app around them
→One team for web, mobile, and the backend
e.g.  Mona Motors — customer app, backend, and dashboards on one stack.
[ 04 — SCALE ]

Data & MVP-to-scale

Data pipelines and infrastructure that take an MVP to something that holds at scale — without a rewrite when the traffic arrives.

→An MVP buckling under real usage
→Data scattered across tools with no pipeline
→Infra decisions that need to age well
e.g.  Event pipelines and Supabase schemas built to grow, not to redo.
// HOW WE ENGAGE
01

Scope

A short, paid discovery to define the problem, the stack, and what “shipped” means.

02

Build

Tight iterations against a live environment — you see it working, not a slide about it.

03

Run

Production hand-off with monitoring, evals, and the option to keep us on the loop.

Which one do you need?

Tell us the problem. We'll tell you how we'd build it — and what it takes to ship.

Start a projectSee the work →