AI Integration
AI that does one job well inside your product, built the way we build it into our own: in the workflow, checked before it lands.
For product teams that have a workflow eating hours every day and want a model to take it over without anyone losing trust in the output. Reading printed forms into structured records, drafting customer communication in two languages, routing tickets, flagging the records that need a human.
We build it the way we built it into StriveBit ERP and Thaalo: the model sits inside the existing step, its output is forced into a schema your database already accepts, a second pass checks the draft against the source, and anything uncertain is flagged for a person rather than silently written. You get an evaluation set and a number you can trust before it goes live.
After launch we keep the prompts versioned, the evals running and the cost per call visible, so a quality regression can be traced and rolled back like any other bug.
How it runs
Find the step
A day with the people doing the work, to pick the one task where a model saves the most hours and the cost of a wrong answer is recoverable.
Schema first
We define the exact structure the output must take, and the checks that run on it, before writing a prompt.
Label and measure
Fifty to a hundred real examples, labelled with your team, become the evaluation set every change is scored against.
Ship with a review loop
Flags, not silent writes. The first weeks run with a person reviewing what the model is unsure of, until the numbers say it can run alone.
Proof: Thaalo menu scan
A photo of a printed menu becomes a live digital menu the same day, with the model checking its own draft and flagging what it is unsure of.
thaalo.inQuestions
Which models do you use?
- Whichever fits the task and the budget. We have shipped on Anthropic and OpenAI models and design so the provider can be swapped. The evaluation set matters more than the model choice.
What if the model gets it wrong?
- It will, sometimes. That is why every output is validated against a schema and anything uncertain is flagged to a person. Nothing the model produces reaches your database or your customers unchecked.
Does our data get used to train anything?
- No. We use API access with training disabled, keep your data in your own infrastructure where it lives today, and only send the model what the task needs.
Building something like this?
Tell us what you're building and we'll give you a straight answer on scope and cost, usually within a day.
Talk to us