How is this different from a generic AI automation agency?

An AI automation agency sells you a team, a retainer, and often a fleet of agents you don't need. This is one senior, founder-led engineer on a flat monthly subscription, building one workflow automation at a time against a real outcome. You talk directly to the person building it, get weekly PRs you review and merge, and can pause anytime — smaller, focused, and implementation-led rather than a sales deck.

Do you build fully autonomous agents that run without oversight?

Not by default, and that's deliberate. Autonomous agents that write to your real systems with no human in the loop are how you get an expensive incident. We build a human-in-the-loop step wherever a wrong action would cost you, with an audit log, approvals, and a kill switch, and only widen the automation once the evals show it's earning that trust.

How do you keep an agent from running up costs or going wrong?

Cost and rate caps, token tracking, retries and fallbacks, idempotent actions, and an audit log of every call are built in from the start. Evals catch quality regressions so you can roll back a bad change, and you watch spend and run history in an admin view instead of finding out on the invoice.

Do I own the code and the automations?

Fully. Everything ships as pull requests into your repository — the agent logic, the integrations, the prompts, the evals — with no proprietary wrapper. When the subscription ends you keep all of it and can run it yourself.

Services - AI agent development services, sized to one senior engineer.

Most AI agent development services sell you a swarm of autonomous agents and a diagram. This is the quieter version that actually ships: one senior, founder-led engineer builds a workflow automation that does one operational job — triage this queue, reconcile these records, draft these replies, keep this dashboard current — wired into the tools you already run, one priority at a time. It's an AI automation build scoped to an outcome, not an agency selling seats.

Start a build How the subscription works

Plans tailored to the build

One senior engineer, one priority at a time

One senior, founder-led engineer takes this build week by week and ships production-ready code as pull requests you review and merge. Time and cost vary by plan and scope, and we’ll cover both before you start.

Discuss the plans How it works

What's included

Workflow automation for real business operations — support triage, admin and back-office tasks, data entry and reconciliation, reporting — where an LLM does the judgement step and your systems do the rest.
Agents that call tools and APIs with guardrails: they read and write to your CRM, database, Slack, email, and internal tools through scoped permissions, with a human-in-the-loop step where a mistake would cost you.
Integrations into the stack you already run — Postgres, Stripe, Slack, HubSpot, Zendesk, internal admin panels — so the automation acts inside your workflow instead of a separate playground.
The reliability layer that keeps an agent from going rogue: retries, fallbacks, timeouts, idempotency, cost and token caps, and an audit log of every action it took and why.
Evals and a review surface so you can see when an automation gets a call wrong, roll it back, and tune the prompt or the rules — not just trust it and hope.
The dashboards and admin controls around it: run history, approvals, overrides, and the on/off switches your team needs to actually let it run in production.

How we build it, week by week

One priority at a time, shipped in reviewable increments you merge as they land — not one big drop at the end.

Week 1 — pick one workflow and de-risk it

We choose the single operational workflow worth automating first, map the steps and the systems it touches, and prototype the agent loop against your real data to get an honest read on accuracy and cost before building around it.

Weeks 2–3 — the reliable automation

The agent and its tool integrations built for production: scoped permissions, guardrails, retries, idempotency, and an audit log, shipped as PRs you review. A human-in-the-loop step wherever a wrong action would be expensive.

Weeks 3–4 — controls, limits, and the edges

Cost and rate caps so an agent can't run up your bill, evals to catch quality regressions, and the admin surface — run history, approvals, overrides, kill switch — that lets your team trust it in production.

Ongoing — expand to the next workflow

Once the first automation earns its keep, the logs show what to tighten and which workflow to automate next. Each becomes the next priority on the board, shipped weekly for as long as the build needs it.

Stack

Next.js / React
Node / Express
OpenAI / Anthropic APIs
Tool/function calling + agent loops
PostgreSQL
Slack / CRM / internal-tool APIs

Is this the right build for you?

A good fit when

You have a repetitive operational workflow — support triage, back-office admin, data reconciliation, reporting — that a well-scoped AI agent could take off your team's plate.
You want the automation wired into the systems you already run, with guardrails and an audit trail, not a standalone chatbot.
You want one senior engineer owning the build week by week and a human-in-the-loop where mistakes cost money.

Not a fit when

You want a fleet of fully autonomous agents running your whole company with no human in the loop — that's a pitch, not a safe production system.
You need a 24/7 managed AI operations team holding the pager — this is code-only, built and handed over as PRs.
You want pure ML research or a custom foundation model — this is applied automation on existing frontier models.

Why on a subscription

Automation work comes in an uneven shape: a hard build to get the first agent reliable and safe, then steady tuning and a new workflow once it proves out. A flexible monthly plan you can pause gives you a senior engineer for the build and keeps them on tap for the iteration — no AI automation agency retainer to negotiate and no ML salary to carry between pushes.

Frequently asked questions

How is this different from a generic AI automation agency?: An AI automation agency sells you a team, a retainer, and often a fleet of agents you don't need. This is one senior, founder-led engineer on a flat monthly subscription, building one workflow automation at a time against a real outcome. You talk directly to the person building it, get weekly PRs you review and merge, and can pause anytime — smaller, focused, and implementation-led rather than a sales deck.
Do you build fully autonomous agents that run without oversight?: Not by default, and that's deliberate. Autonomous agents that write to your real systems with no human in the loop are how you get an expensive incident. We build a human-in-the-loop step wherever a wrong action would cost you, with an audit log, approvals, and a kill switch, and only widen the automation once the evals show it's earning that trust.
How do you keep an agent from running up costs or going wrong?: Cost and rate caps, token tracking, retries and fallbacks, idempotent actions, and an audit log of every call are built in from the start. Evals catch quality regressions so you can roll back a bad change, and you watch spend and run history in an admin view instead of finding out on the invoice.
Do I own the code and the automations?: Fully. Everything ships as pull requests into your repository — the agent logic, the integrations, the prompts, the evals — with no proprietary wrapper. When the subscription ends you keep all of it and can run it yourself.

More we build

Got a project? Let's ship it.

3 spots open. Tell us what you need shipped. We’ll match the plan and timeline to the work on a short sales call, then deliver it in reviewable increments.

Start next week