AI consulting and workflow design
Workflow audits, AI roadmaps, and build-vs-buy decisions from an implementation shop that ships the first system inside the engagement.
AI consulting here means a workflow audit that ends in working software, not a slide deck. We map where AI fits in your business, where it does not, and what the first system should be, then build that system inside the same engagement. It is for owners and operators who have been pitched AI several times and want to know what is actually worth doing.
The problem
The usual AI engagement produces a roadmap, a maturity model, and an invoice. Nothing runs at the end of it. The gap is not strategy. It is that the people writing the strategy cannot build the thing.
- Recommendations arrive as categories ("document automation") instead of a named system in a named tool.
- Nobody checks whether the data the plan depends on is clean, accessible, or even collected.
- Pilot projects get chosen for how well they demo, not for how much manual work they remove.
- The build-vs-buy question gets answered by whoever is selling.
- Six months later the team has three AI subscriptions and the same manual process.
What we build
A workflow map
The actual steps, systems, handoffs, and decision points of the process you want to improve. Written in plain English, verified with the people who do the work.
An honest opportunity list
Which steps AI genuinely helps with, which need a deterministic automation or a SQL query instead, and which should stay manual because judgment matters.
A build-vs-buy call
Where an off-the-shelf tool is the right answer, we say so and help you pick. Custom work is only worth it when the workflow is specific to your business.
The data and integration plan
What data the system needs, where it lives today, what has to be cleaned or connected first, and what that work involves.
The first working system
The smallest useful version, built and running in your stack before the engagement ends. Not a prototype on our laptop.
A cost and failure model
What it costs to run per month, what happens when the model is wrong, and where a human stays in the loop.
What you get at handoff
- The workflow map and the decision record, so the reasoning survives staff changes.
- Working code in your repository, running in your cloud, calling your accounts.
- A runbook covering normal operation, failure modes, and who to call.
- Training for the people who will use and maintain it.
- A prioritized list of what to build next, with rough effort for each.
Stack
Models
Claude, OpenAI, Open-weight models where privacy requires it
Languages
Python, SQL, TypeScript
Data
Postgres, Snowflake, BigQuery, dbt
Orchestration
Airflow, Scheduled jobs, Webhooks
Where it runs
AWS, GCP, Vercel, Your accounts
Related services
FAQ
What happens in the first two weeks?
A paid kickoff. We interview the people who do the work, map the workflow, look at the real data behind it, and come back with a written recommendation: what to build first, what to skip, what it costs to run, and what could go wrong. If the honest answer is that you do not need AI, that is what the document says.
Do you actually build, or do you hand off a plan?
We build. The first working system ships inside the engagement, in your repository and your cloud. A recommendation we cannot implement ourselves is not a recommendation we make.
What if the answer is that AI is the wrong tool?
That happens regularly and we say so. A scheduled job, a cleaned-up SQL model, a better form, or a fixed integration solves a lot of problems that get pitched as AI problems. You still get the workflow map and the plan, and we can build the simpler fix instead.
How much time does this take from my team?
Expect a few hours from the people who do the work during discovery, and a technical contact who can grant access to systems. Less than a software rollout, more than zero. We do not need a steering committee.
Do you work with businesses that have no technical staff?
Yes. Many engagements start with an owner or operator who knows exactly where the process breaks but not which tools should be connected. We translate that into a build plan, and we write the handoff documentation for the team you actually have.
What makes a project a bad fit?
Projects where nobody can describe the current process, where the data does not exist yet, where the goal is a demo for a board meeting, or where the real problem is organizational rather than technical. We would rather tell you that early.
Ready to scope AI Consulting?
Send the workflow, tool stack, or reporting problem. We will tell you what should be automated, what should stay manual, and what is worth building first.