A senior engineering partner for your AI product, by the month
Architecture, stability, scaling and cost control on subscription. A senior team takes technical ownership of your AI product without the cost or wait of a full-time CTO hire.
Discuss a pilot →Quick facts
- Business size
- Startups and scale-ups running an AI product without a senior ML or platform lead in house
- Timeline
- Ongoing, month to month
- Budget range
- Monthly retainer, scoped by conversation
- Hardware
- Your existing cloud and stack, we work inside it
- Data needed
- Access to your codebase, infrastructure and roadmap
- Evolution
-
- Genesis
- Custom-built
- Product
- Commodity
No product gives you this. We assemble and train it around you.
What this scale means
Further right means more proven and cheaper. Further left means newer and riskier. Here is the test for each step.
- Commodity
- You could get the result yourself from a ready service, with almost no work. We rarely take these on.
- Product
- A vendor already sells this result turnkey, like shelf recognition from Trax or document reading from ABBYY. If one of them fits you, use it. You come to us when it does not: when it has to run on your own servers, cost less, or fit systems the product cannot reach.
- Custom-built
- Vendors sell only the parts. A tool like Tableau hands you charts, but the dashboards and metrics for your business still have to be built. That build is the work, and that is us.
- Genesis
- The approach exists but does not work reliably yet. You are betting on it maturing, so it costs more and carries more risk.
Expected outcomes
The Problem
An AI product needs senior engineering long before it can justify a full-time CTO. The model has to scale. The inference bill has to stay sane. The data pipeline has to keep running. And someone has to make the architecture calls that are expensive to undo later. Founders often carry this themselves. Or they hand it to a strong junior team that ships fast, then hits a wall on scale, cost or reliability.
What You Get
A senior engineering partner on a monthly basis, who takes ownership of the technical side of your AI product:
- Architecture. The structural decisions: where the model runs, how data flows, what to build and what to buy.
- Stability and scaling. Making the system hold up as traffic and data grow.
- Cost control. Watching the cloud and inference bill, which is often the quiet killer of an AI product’s unit economics.
- A second set of senior hands. Code review, hiring help and a sounding board for your existing engineers.
How It Works
You keep your team and your roadmap. We plug in as the senior technical partner, on a retainer scoped to how much ownership you need. Some months are heavy on architecture, others on cost or a scaling push. The arrangement is month to month, so it grows or winds down as your in-house seniority does.
Where It Fits
This makes sense if you…
- Run an AI product without a senior ML or platform lead in house
- Are scaling and feeling the cost or reliability pressure
- Want senior ownership without committing to a full-time executive hire
This is probably not the right fit if you…
- Already have a strong senior engineering leader in place
- Need a fixed-scope build, with a clear start and end, more than ongoing technical ownership
FAQ
How is this different from hiring an agency to build something?
A build has a fixed scope and an end. This is ongoing technical ownership: the architecture, the cost and the scaling stay our concern month after month.
Will you replace our engineers?
No. We work alongside your team and make them stronger. That means senior review, hiring help, and the architecture calls that are hard to make from the inside.
How do you price it?
A monthly retainer, scoped by conversation to the level of ownership you need. There is no fixed package, because the right level changes as you grow.
Ready to Discuss?
If your AI product needs senior engineering ownership but not a full-time CTO yet, we will scope a retainer that fits where you are.
