Four kinds of system. All of them yours.
Custom AI applications
Product-grade systems with a model at the core: retrieval, evals, guardrails, UI. Not a chatbot bolted onto a CRUD app.
Workflow automation
Your tools already hold the data. We make them act on it with API-level integrations, not brittle no-code chains someone has to babysit.
Stack consolidation
Seven subscriptions doing one job, joined by spreadsheets. We replace the seams with one system you own outright.
Lead-gen & content tooling
Pipelines that source, score, write, and send. Measured on replies and pipeline, never on impressions.
Five systems, drawn as they execute.
Hover any step to see what it runs on.
Process as architecture.
Map the system
Every input, owner, and failure point documented before a line of code exists.
Design the seams
Where systems connect matters more than what's inside them. We design those joints first.
Build load-bearing pieces
Nothing ships that can't take real traffic on day one. No throwaway prototypes disguised as product.
What people ask before scoping one.
What's included in a fixed-price AI pilot?
One workflow taken end to end, for a fixed $3,000–$6,000 over two to three weeks. That covers the system itself, the integration into wherever the work already happens — the CRM, the Slack channel, the shared drive — and the unglamorous reliability work: retries, rate limits, a cap on model spend, and a defined behaviour for every failure path. The repository sits in your account from the first commit. What it does not include is a discovery phase, a deck, or a prototype that needs a second budget to become real.
How do you decide which workflow to automate first?
We pick the one that repeats the most and annoys your team the most, not the one with the best demo. Every input, owner and failure point gets mapped before any code exists, which usually takes days rather than weeks. A narrow first system that ships and gets used is worth more than a broad one that stays in review.
What does the system cost to run after it ships?
You pay your own model API and hosting bills directly, and nothing to us for the software itself. There is no per-seat licence and no platform subscription, because the code is yours and runs in your accounts. Model usage is normally the largest line, which is why a spend cap and a fallback path are built in during the pilot rather than added after the first surprising invoice.
What happens when the model gets something wrong?
Every path has a defined behaviour for being wrong, and the ones that matter keep a human in the approve seat. Anything the system isn't confident about escalates instead of guessing, drafts are attached for review rather than sent, and when the model is slow, down, or refuses, the system does something sensible rather than showing your operations lead a stack trace.
Do we have to replace the tools we already use?
No. We build around your existing stack through its APIs, so the AI shows up inside the tools your team already opens. Most engagements start by wiring into what's there. Consolidation only comes up when several subscriptions are doing one job and being joined together by a spreadsheet.
Do you build on no-code platforms?
No. Integrations are written at the API level, in code you own, because no-code chains break quietly and then need someone to babysit them. The distinction matters most at handover: a repository can be read, tested and changed by any developer you hire later; a canvas of connected boxes in someone else's product cannot.
Who runs the system after handover?
Your team does, and the handover is built for that. The repository is in your account, it deploys on your infrastructure, and the cutover includes monitoring and a runbook rather than a verbal walkthrough. If you want us to keep operating and extending it, that runs as a monthly retainer scoped per engagement — but it's an option, not a dependency.
You already know what to build.
Send the two-paragraph version. You'll get a real technical response, not a calendar link and a discovery questionnaire.