We build the AI. You run the business.
Operator-grade systems, delivered in weeks, not quarters — wired into the tools your team already runs. No slideware. No demos that die. Code you own the day we hand over.
Every engagement is bespoke but fits one of these shapes. We pick the smallest one that solves the problem, then ship it end-to-end.
A short discovery call, a one-page spec, a 2–6 week build with weekly demos, then a clean handover. Every engagement, same shape.
We map the problem together. You describe the pain. We ask the uncomfortable questions — what does success actually look like? — and tell you honestly whether we're the right fit. If we're not, we point you to someone who is.
Fixed scope, fixed price, fixed timeline. A single page describing exactly what we're building, the acceptance criteria, and what you'll own at the end. If it won't fit on a page, we scope it smaller.
We build in your stack, on your infra, with your keys. Every Friday you get a working demo, a Loom walkthrough, and a raw repo link. You see the code as it exists, not a polished screenshot from a designer.
Clean handover: repo, deploys, keys, docs, runbook, eval suite. We walk your team through it until they can operate solo. Then we stick around for 30 days of free bugfix + office hours. After that, you decide if you want us close.
We sell you a working system tied to a business outcome. Here's the shape of what you walk away with.
Work that used to route through three humans now routes through one human + a copilot. Your best people stop being a bottleneck and become a leverage point.
The Loom your team never watched is now a running system. New hires ramp in days, not months. The process doesn't drift when someone leaves, because the process is the code.
Weekly ops reports, sales debriefs, customer summaries — written by the system that already has the data. Your Monday morning becomes reading instead of writing.
We work with people who run real businesses and know exactly what's broken. If you can describe the problem in one sentence, we can scope a fix in one page.
Your v1 works. Now you need AI in it before your competitor ships theirs. You don't have time to hire an ML team — you need something shipped in weeks, integrated into the thing you already have.
You've tried to hire. You've tried to document. The work keeps piling up. You know half of it could be automated if you had someone technical who actually understood the domain.
Last time someone promised you AI they delivered a slide deck. This time you want a working system in production with your team's hands on the keyboard. That's the engagement we run.
Short operator reports from engagements we've shipped. What we tried, what broke, what we'd do again.
Most RAG failures don't come from the model — they come from the chunker. We walk through a client case where switching chunk strategies cut hallucinations by 68% overnight, and why your eval suite missed it.
read dispatchLong responses, robotic tone, repetition loops, failure to wait for speakers. We catalog the common failure patterns from 12 voice agents we've shipped, and the exact prompts + settings that fix them in production.
read dispatchWe replaced our 18-slide proposal with a one-page spec doc and closed more work, faster. Here's the template we use, why clients prefer it, and the one section we refuse to remove.
read dispatchIf yours isn't here, the 30-minute discovery call is the fastest path to an answer. No sales funnel, just a conversation.
Postgres + Rails, we ship in Postgres and Rails. If you run Supabase + Next.js, we ship in Supabase and Next.js. The exception is AI infra — we'll recommend Claude, OpenAI, or open models depending on the task, and defend the choice.