About
A small, senior team allergic to theater.
DPR Labs is built for founders and operators who have seen the AI demo, felt the room get excited, and then watched the thing die three weeks later.
We are not trying to be a large firm. We are a small, senior AI studio that takes narrow bets: one workflow, one number, two weeks, fixed price, refundable if we miss the agreed outcome. That shape is not a gimmick. It is a forcing function. It keeps the work honest enough that a smart client can judge it without a twelve-person committee.
Our point of view is simple: most companies do not need a transformation program. They need one painful workflow made measurably better, owned by their team, with the code and evaluation work handed over. If that first bet wins, you have earned the right to do the next one.
Small by design
Small, senior, and allergic to theater.
A two-week bet with a refund on the line is not a job you hand to a pyramid of juniors billing by the hour. It is a job for the person who has already shipped similar systems and knows on day two whether the shape is wrong. We stay small because the work gets worse when the people selling, managing, and building are all different rooms.
Small does not mean casual. It means fewer handoffs, faster truth, and less room for ceremony. When a retrieval system is wrong, a metric is fake, or an integration is one click too far away, the senior person doing the work sees it directly. There is no account manager translating pain into a ticket and no deck pretending that ambiguity is strategy.
This costs us scale. We cannot run twenty pilots at once, and we will not pretend we can. But for a founder or operator making a two-week decision, that is the feature. You want the person who can say no early, not a large team learning on your budget.
No-list
What we will not do.
The no-list is the most honest thing on this site. It protects you from buying the wrong help and protects us from shipping work we would be embarrassed to measure.
- Staff augmentation where we become extra hands without owning an outcome.
- Six-month “transformations” that start with workshops and end with a roadmap.
- Projects with no baseline data or no practical way to collect it.
- Teams that will not name the number before the build starts.
- “Make us AI-first” mandates with no workflow, owner, or user behavior attached.
- Work where nobody on your side will own the result after handoff.
Saying no loses revenue in the short term. It also keeps the method true. If the work cannot be measured, owned, and handed over, it is not a DPR pilot.
Principles
Our five principles, and what each costs us.
Principles are cheap when they are only adjectives. Ours matter only because each one makes some money harder to take.
Agreed up front.
We write the metric before we build, even when a vague scope would be easier to sell and easier to declare a win.
No rented black box.
You get the code, prompts, evals, docs, and handoff. Lock-in would be more profitable. It would also make the work weaker.
Caveats in plain sight.
We show baselines, sample sizes, misses, and limits, even when a prettier number would close faster.
Revenue is not a reason.
We say no to work with no owner, no metric, or no sane path to production, even when we could use the invoice.
Refundable by design.
The refund puts our money on the outcome. That is only possible because the scope is narrow and measurable.
The team can run it.
Documentation is not an afterthought. If your team cannot operate the result, we built a dependency, not a capability.
Pricing
How we price, and why.
Most pilot pricing is vague because the work is vague. We go the other way. A pilot is fixed, narrow, and tied to one measurable outcome. Most two-week pilots land around $8k–$15k, depending on integration difficulty, data readiness, and how much handoff work is required.
The refund matters because it changes the conversation. We cannot hide behind hours burned or “strategic learnings” if the agreed number does not move. But the refund is only possible because the scope is disciplined. One workflow. One owner. One baseline. One testable result.
That means we will sometimes tell you the right answer is not a pilot. Maybe the data is not ready. Maybe a rules script beats a model. Maybe your team needs to pick an owner before outside help makes sense. Those answers are less exciting than a proposal. They are also cheaper.
We are wrong for companies that want a slide-heavy transformation program, a permanent vendor dependency, or a broad “AI strategy” with no operating number attached. We are right for teams with a painful workflow, a decision-maker close to the work, and enough urgency to measure the before and after.
If this sounds familiar
Bring us the workflow nobody wants to own.
If it has a baseline, an owner, and a number worth moving, we can usually tell in one call whether a two-week pilot is a good bet.