A focused product feature
One AI feature, such as drafting, search, comparison, or setup help, built into your existing application.
AI product features
We add search, drafting, extraction, or analysis to your existing product. Users can review and correct results within the interface they already use.
ScopeOne workflow or several connected applications
Delivery timingDays for a focused prototype, weeks for a well-defined release when access and decisions are ready
How we check itWe test the feature on the original user task and compare it with doing the same task without AI.
Add AI to a task users already do
We look for a step where your users already get stuck and build the AI help into that part of the product, using its existing screens and permissions. Then we test whether it helps them finish the task before widening its scope.
Good fit
- SaaS products with a task users struggle to complete
- Industry software teams with specialized requirements
- Products where users still do setup or analysis by hand
Not the right fit
- Adding AI just to say the product has it
- Features not tied to a specific user task
- Open-ended generated content where every answer must be correct
What you get
User controls
Preview and editing, feedback, usage limits, and a clear way to continue when the model cannot help.
Release checks
Tests based on real product tasks, plus monitoring of quality, response time, and usage cost after launch.
How it works
Choose the task
We look at where users get stuck and choose one step to improve with your product team.
Prototype inside the flow
We build a prototype inside your product, using its data, sign-in, and interface patterns.
Release to a defined audience
We release it to a limited group first and compare task completion and support issues before wider access.
Scope, cost, and ownership
What we need from you
- An existing application and a specific user problem
- Approved product data and access to user feedback
What affects cost
- Depth of application integration
- Separation of each customer’s data, and response-time requirements
- Model usage, testing, and rollout complexity
Technical scope
- Product data access for the model
- Streaming responses
- Routing requests between models
- Usage limits
- Task-based evaluation
- Privacy and separation of customer data
Support and maintenance
Your product team decides how the feature should behave. We agree who investigates bad responses, adjusts usage limits, and tests changes to the model.
Common questions
Can you work inside our application?
Yes. We work within your design system, sign-in and permissions, data formats, and release process.
How do we avoid provider lock-in?
By keeping your product logic and tests separate from any one provider’s . Alternative models can then be tested against the same cases.