How we work
What we think, what we ask before we recommend anything, and how an engagement runs.
The problem in your words
Before we talk about AI, we listen to the people closest to the problem: what happens today, where it breaks down, and what would make the work better. What we build has to answer to that.
Tell us what you are trying to do, what is in the way, and what you have already tried. We ask the people doing the work where the documented process differs from the one they follow, and what a useful result would look like to them.
Together, we define the problem the project needs to solve and how we will know it helped. That gives us a basis for deciding what to build, what to leave alone, and whether AI belongs in the solution.
Positions we hold
We do not take engagements whose stated goal is workforce reduction. You cannot extract institutional knowledge from the people you are eliminating, which is why headcount-justified AI projects tend to fail. If reduction is the objective, we will say so on the first call.
We find the root cause first, then determine the tool. Sometimes the tool is not AI. A firm that names the answer before it knows the question is selling something.
A large share of what ships as an agent system is a scheduled job with a model call in it. The orchestration layer adds failure modes and hides where things break.
We hold no vendor relationships that pay us, and we deliver on AWS, Azure, Google, and on premises. Where your systems run stays a decision rather than a constraint we imposed.
No account layer between you and the person making technical decisions. We are a small senior team by choice, not by stage.
Automating a bad workflow just makes it generate errors faster. We map the operational reality before writing a single line of code, because applying a brilliant model to a flawed system is a waste of money and time.
Six questions before any recommendation
Not a discovery formality. Most AI projects that fail do so for reasons visible in the answers.
- 01
What does your data look like?
Not the schema. How many systems hold the same customer under different identifiers, how much context lives in documents nobody indexed, and how far the process people follow has drifted from the one written down.
- 02
What happens when it is wrong?
Every model is wrong at some rate. A system that drafts internal summaries and one that touches customer commitments have different tolerance for error, and should not be built the same way.
- 03
Who maintains this in eighteen months?
If the answer is a person who has left or nobody in particular, that shapes what we should build. Systems nobody can maintain are liabilities regardless of how well they work on day one.
- 04
What does this cost at a hundred times the volume?
Costs that are trivial in a demo are line items in production, and the architecture that is cheapest at pilot scale is often the most expensive at real scale.
- 05
What already exists?
Most organizations have more than they think, and some of it works. Replacing a functioning system because it is unfashionable is a real and common way to spend a year.
- 06
Who has to change how they work?
The technical risk is usually smaller than the adoption risk. A system nobody uses failed regardless of whether it works.
The mechanics
Tell us what you are trying to do and what is in the way. We will tell you whether it is something we should work on, and if it is not, where to look instead.
The first statement of work defines deliverables and schedule. You know what you are buying before the work starts, and what triggers a separate quote.
Six months in, you know things you did not know at the start. A plan that does not change over that period was not being tested against reality.
Consulting concludes at six months, built to be handed to your team with documentation. Managed Intelligence continues as long as you want the software. Different products, different postures, and we would rather say so plainly.
Reasons to hire someone else
Your goal is reducing headcount
See above. We will say so on the first call.
You want to be told AI is the answer
We may conclude it is not.
You want the lowest-cost option
We are not it, and firms that are will tell you so.
Start with a conversation
If what is on this page sounds like how you want to work, tell us what you are trying to do.