AI Solutions
for Business

An unrestricted model, yes, it will. That's why we build on RAG: the assistant answers only from your documents and cites its source. If the answer isn't in the knowledge base, it says so instead of making one up.

No. We use the API with training on your data turned off, and we strip sensitive data before it's ever sent. If needed, we can run the model inside your own environment.

We start with a pilot on your real data: we take a sample of tickets or documents, run it through, and measure accuracy. You see the numbers before you commit to a full rollout.

On top of development, there's a cost for the models themselves — usually in the tens to low hundreds of dollars a month, depending on volume. We set spending limits and show usage in the dashboard, so there are no surprises.

Start with whatever routine task annoys you the most. Usually that's either searching for information or moving data out of documents. We take one such area, test it on real data, and look at the numbers — instead of starting by buying a platform.

Yes. If the data can't leave your company, we run the model on your own server. Quality will be a bit lower than the largest cloud models, but nothing leaves your perimeter. The right choice depends on what kind of data you're handling.

That's exactly why, in customer-facing scenarios, we limit it to your own materials and keep a hand-off to a human. The AI answers questions it can find in your documents, and honestly passes everything else to a person.

Partly, yes — which is why we start by measuring it on your own data. If the test shows the quality isn't there, or the savings don't cover the cost of building it, we'll tell you and walk away. That happens, and it's a perfectly normal outcome.