DELIVERY · 4–6 WEEKS · FIXED FEE
AI automation services that ship one production system in 4–6 weeks.
I scope one workflow automation, engineer it, integrate it into your systems, train your team, and hand it off. One fixed fee. One concrete deliverable that runs in production.
WHAT IT IS
One thing. In production. Not a prototype.
Most AI projects stall between proof-of-concept and production. They produce demos that live in notebooks, not systems that run in the real workflow. Someone else makes an impressive video. Nothing shows up in your daily tooling.
The Automation Sprint is structured to avoid this. I pick one high-priority automation candidate — usually surfaced through a Workflow Audit or an internal brief your team already has — and I engineer it to production quality. That means reliable, tested, monitored, integrated, and documented. Not experimental. Not "let's see what happens."
At handoff, your team can run it, monitor it, and modify it without me. That's the benchmark I build to. If I can't hand it off cleanly, I haven't finished the engagement.
- Monitoring
- You can see it running, and you find out it stopped from an alert rather than from a colleague.
- Error handling
- Defined behaviour when an input is malformed or an upstream service is down. Failures are logged and recoverable, not silent.
- Human review
- The steps where a person approves before anything irreversible happens are decided with you, not assumed away.
- Permissions
- It runs with the access it needs and no more, under credentials your team controls.
- Documentation
- A runbook covering how it works, how to change it, and what to do when it breaks at 2am.
- Ownership
- It runs on your infrastructure, under your accounts. Nothing here depends on me still being around.
Weighing whether to build internally instead? Read the agency vs in-house comparison, or start with the AI workflow automation guide.
WHO IT'S FOR
You know what to build. You want it built well.
Right fit if…
- You have a clearly scoped automation target
- Your internal team can't spare the bandwidth to build it
- You want production-grade quality, not a demo
- You want full ownership and handoff — a system your own team can run
Probably not a fit if…
- You haven't identified which workflow to automate (start with the Audit)
- You need someone to operate the system long-term (I hand off, I don't operate)
- You need a large multi-system overhaul (scope to one thing and expand from there)
WHAT'S INCLUDED
From scoping call to production system.
Scoping document
Detailed specification of the automation: inputs, outputs, integration points, expected behavior, failure modes, and success criteria.
Production automation
Fully engineered, tested, and deployed to your infrastructure. Not a wrapped ChatGPT call — proper pipeline, error handling, logging, and monitoring.
Integration into your existing stack
Wired into your current tools — CRM, ERP, email, internal APIs — not a standalone experiment that requires its own access spreadsheet.
Full technical documentation
Architecture diagrams, environment setup, data flows, prompt templates (where applicable), and runbook for your team.
Team training session
One or two hands-on sessions with the operators who will use the system daily — not a slide deck, a working walkthrough.
30-day post-launch support window
Bug fixes and critical adjustments within 30 days of handoff, at no additional cost. Edge cases always surface in the first month.
PROCESS
Four to six weeks. Fewer meetings than you expect.
Week 1
Scope lock
Finalize the spec, agree on success criteria, access credentials, and integration targets. Following an Audit this week is shorter: the storyboard already describes what gets built, so the work starts from a design instead of a blank page.
Weeks 2–3
Core engineering
Build and test the automation pipeline in a staging environment. Weekly check-in call to align on progress.
Week 4
Integration & hardening
Connect to production systems. Load test. Fix edge cases. Write the runbook and documentation.
Weeks 5–6
Handoff & training
Go live, train the team, close open issues, and transfer all assets and credentials to your team.
OUTCOME
A system your team can run without me.
The goal isn't a working demo. The goal is a running system that survives the first 90 days in production — including the edge cases, the user errors, and the scenario where the API key expires at 3am on a Tuesday.
The metric to hold the Sprint to is hours saved per week on the automated workflow. Agree the number before the build starts and measure it after launch.
Everything is fully transferable. Source code in your repository. Credentials in your vault. Documentation in your wiki. If you decide to bring all future AI work in-house, you have everything you need to do that. The content pipeline in the portfolio was built the same way.
FAQ
Common questions.
What does a Sprint cost?
Flat fee, scoped per engagement based on complexity and integration surface. I'll quote it after the scoping call.
What technologies do you use?
Python, TypeScript, and whatever LLM fits the task (OpenAI, Anthropic, or open weights). The automation integrates with anything API-accessible.
What if we need more than one automation?
Start with one. Get it running well. The second is always easier to justify — and to budget for — once the first one is saving real time.
Do you run it after handoff?
No. I hand off completely, and running the system day to day is not on offer — if you need that, I can point you to managed service providers. Standing ownership of the AI decisions is a different thing, and that is what the Fractional Chief AI Officer engagement covers.
What infrastructure do we need?
I work within your current stack. If you're on AWS, GCP, or Azure, I deploy there. If you need guidance on cloud setup, I'll include that in scoping.
Can we run a Sprint without a Workflow Audit?
Yes, if you already have a clear and well-scoped target. Many clients come to the Sprint directly with their own internal analysis.