AI Products & Platforms
AI Where It Removes Work, Nowhere Else
The useful question is not what AI could do in your product. It is which step your users currently dread, and whether a model can take it off them reliably enough to trust.
What the Engagement Actually Covers
Finding the step worth automating
We look for the task that is repetitive, judgement-light and currently expensive. That is where a model pays for itself; everywhere else it is a demo.
A grounded pipeline, not a bare prompt
Retrieval over your own data, structured output the rest of the system can rely on, and validation on the way out.
A human in the loop where the cost of wrong is high
Draft-and-approve rather than fire-and-forget, until the measured accuracy earns the autonomy.
Honest failure states
What the feature does when it is not confident, when the provider is down, and when the user pastes something absurd.
When to Buy This, and When Not To
This is for you if
- Your users do something repetitive inside your product
- You have proprietary data a model could reason over
- Support is answering the same question hundreds of times
This is not for you if
If the honest answer to "what does this save the user" is "it is impressive", do not ship it. Novelty features get opened once.
Projects That Used This
Marketing SaaS
Blogy
Our own product: connect a CMS once, and it researches, writes and schedules on its own.
Read the case study
Lead intelligence
Mantis Ai
Our own product: real-time map search that finds local businesses without a website.
Read the case study
Reputation product
Dhando
Our own product: more genuine Google reviews, from a single link.
Read the case study
What Clients Ask Before Signing
Will our data be used to train someone's model?
Not on the enterprise API tiers we use, and we will show you the provider's terms in writing. Where it matters we can run an open model in your own cloud instead.
How accurate is accurate enough?
It depends entirely on what a mistake costs. We set the threshold with you first and measure against it, rather than shipping and hoping.
Can you work with our existing engineering team?
Yes, and it is often the cheaper arrangement — we build the AI layer and hand it over with the eval suite.
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