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LLM integrations, retrieval-grounded assistants, internal copilots, customer chatbots and document intelligence — built so every answer can be traced back to the source it came from.
A general-purpose model knows a great deal and nothing about your business. Asked about your refund policy it will produce something plausible, confident and wrong. The engineering that makes generative AI usable in a company is almost entirely about closing that gap: retrieving the right passage from your own material and requiring the answer to come from it.
That is why every assistant we build cites. If the answer cannot be traced to a document, a policy or a record, the assistant says it does not know — which is a far more useful behaviour than a fluent guess, and the one your support team can actually stand behind.
The passage the answer was built from is shown beside it, so a reader can check rather than trust.
Outside its material, the assistant says it does not know and points at who does.
A defined handover path with the conversation attached — not a dead end with a chat bubble.
An admin screen shows what was retrieved for a question, which is how a wrong answer gets fixed.
Per-conversation and per-tenant ceilings, with caching on repeated questions.
Model access sits behind our own interface, so a provider change is configuration rather than a rebuild.
All of it grounded in content you control, with the source shown beside the answer and an admin screen for the people who maintain that content.
The model is a component. What makes the system safe to put in front of customers is the layer around it, and that layer is where the engineering time goes.
A grounded assistant is exactly as good as the material it reads. If your policies contradict each other, the assistant will faithfully reproduce the contradiction. Part of the engagement is therefore a content review, and we would rather raise that at quoting time than deliver something that is technically working and practically useless.
An organisation with a body of its own material, such as policies, manuals, contracts, tickets or product data, that staff or customers keep asking questions of: a support team answering the same questions every day, an internal team searching documents, or an operations team extracting fields from forms and invoices.
It needs that material to be reasonably current, because a grounded assistant quotes what it reads. Where it is not, the engagement includes a content review.
Straight answers, including the ones that rule us out.
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