For founders planning an AI feature
Find out what your AI feature will take before you commit to building it
Pose analysis, food recognition, recommendations and AI agents sound simple in a pitch deck. What they cost depends on questions a sales call can't answer: what data exists, how accurate the feature has to be, and whether it runs on the phone or a server. This five-day sprint answers those questions and ends with a written scope and a fixed quote. The fee is credited toward the project if you go ahead.
What you get
What’s included
Feature definition
We pin down what the feature does for the user and what 'good enough' means in practice.
Data assessment
What data you have, what you would need, and whether existing models can do the job before anyone trains a new one.
Realistic accuracy
The accuracy to expect in real conditions, like poor lighting or a phone propped on the floor, and whether that is good enough for the feature.
Architecture options
On-device versus server, which model approach fits, and what each choice means for cost, speed and privacy.
Written scope and quote
A scoped plan with milestones and a fixed quote for the build.
A clear go or no-go
If the feature isn't worth building yet, we say so and explain what would need to change.
A good fit if
- Fitness app founders who want camera-based form feedback, rep counting or body tracking
- Health-tech startups with an AI feature on the roadmap and no grounded cost
- Teams holding quotes for the same AI idea that are far apart
- Founders who need to know whether a feature is worth building yet
Not included
- Building or training the model. That is quoted in the scope.
- Collecting or labeling training data.
- Scoping the rest of your app, which the MVP Planning Sprint covers.
- Clinical validation or regulatory review of any medical claims.
How it runs
From kickoff to handover
- Day 1
Kickoff and feature definition
We walk through the idea with whoever owns it and agree what the feature must do and how success is measured.
- Day 2
Data and model review
We review the data and sample media you have and the existing models that could do the job.
- Day 3
Feasibility checks
Where it can be done quickly, we test the most uncertain part against existing models or sample data, so the accuracy estimate rests on evidence.
- Day 4
Architecture and cost
We compare on-device and server options and work out what each costs to build and run.
- Day 5
Scope, quote and walkthrough
You get the written scope, the quote and our recommendation, and we take you through it on a call.
Questions
Questions about AI/ML discovery
Why not quote the feature on a sales call?
Because its cost depends on what data exists, what accuracy it needs and where it runs. The sprint answers those questions in five days, and we stand behind the quote it produces.
Is the fee credited if we go ahead?
Yes. The sprint fee is credited toward the project, so it costs nothing extra if you proceed with us.
What if the answer is that we shouldn't build it?
Then you know after five days and $1,500, with no build money spent. You keep the written findings and can use them however you like.
Which AI features does the sprint cover?
Computer vision features such as pose estimation, form feedback, rep counting, food recognition and body tracking. Also recommendations, adaptive programming and conversational AI agents inside your product.
What do you need from us during the week?
Time with whoever owns the product idea on day one and day five, any data or sample media you already have, and access to your current app or designs if they exist. Quick answers to our questions keep it to five days.
How is this different from the MVP Planning Sprint?
The MVP Planning Sprint scopes a whole product. AI/ML discovery goes deep on one AI or ML feature, which is usually where the cost risk sits. If you're building a new app with an AI feature at its center, we'll suggest which to start with.
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Ready to start AI/ML discovery?
Tell us about your business. We'll confirm the scope and send you a start date.
