A private AI assistant for the documents
you could never paste into a chatbot.
Contracts, financials, client files, HR records and strategy documents stay inside a private environment in your own cloud account. Your team asks questions in plain language and gets answers with citations to the exact source passage. Every question is logged. Nothing trains anyone else's model, and nothing crosses the boundary.
Your team is already using AI on company documents
The only question is whether it happens inside a boundary you control, with a log, or on a public chatbot without one.
A contract clause pasted into a consumer chatbot to get a summary. A client spreadsheet uploaded to check a formula. A draft offer letter polished by a free tool. Each one helpful, each one outside the business, each one unlogged.
Nobody is leaking on purpose. The public tool is fast and the policy memo is not. Banning the tools does not work; staff route around bans. The fix is a private tool that is as fast and is inside the perimeter.
A private assistant that reads your documents, answers with citations and keeps a log, deployed in a cloud account the business owns. Staff get the speed. The owner gets the boundary and the record.
How the assistant works
Contracts, policies, financials, client files, whatever you choose to include, are indexed in a private store inside your own cloud tenant. Access follows the permissions you already have: a person sees answers only from documents they could already open.
"What are the payment terms in the Harbor contract?" "Which clients have a renewal in March?" "Summarize the last three board updates on hiring." Questions are typed the way people speak, in a chat window inside the tools they already use.
Every answer points to the passage it came from, document and page. Your team verifies instead of trusting. When the documents do not contain the answer, the assistant says so rather than inventing one.
Who asked what, when, against which documents, with what answer. The log is yours, encrypted at rest and in transit, exportable at any time. It is the record you would want if a question about data handling ever arrived.
Nothing leaves your cloud account
The architecture is the policy. The assistant runs where your documents already are, and the model it uses never trains on them.
The index, the application and the logs live in a cloud account the business owns and can inspect. INNOVIZZ builds it there and hands over the keys.
The assistant uses language models through enterprise terms under which prompts and documents are not retained for training. Your contracts never become part of anyone's model.
The subscription earns itself every month or you leave with everything: the index, the logs, the configuration. There is no platform of ours holding your data.
The questions it answers on a normal Tuesday
The value is not a dramatic demo. It is the forty small questions a week that used to mean opening six files or asking the one person who remembers.
Before you decide
Plain answers to the questions that come up in the first ten minutes of every discovery call.
What is a private AI assistant for small business?
An AI assistant that runs inside your own cloud account, reads only the documents you give it, answers with citations to those documents, and logs every question. The difference from a public chatbot is where it runs and what it remembers: your tenant, your documents, your log, no training on your data.
Is it as good as the public chatbots?
For questions about your own documents, it is better, because it has them and they do not. For general knowledge it uses the same class of models. What it will not do is invent an answer when the documents do not contain one; it says so instead.
Who can see what?
Access follows the permissions you already have on the documents. A person receives answers only from documents they could already open. The owner sees the full log.
How is it deployed?
INNOVIZZ builds it in your cloud account, indexes the document sets you choose, connects it to the chat tool your team already uses, trains the team in a session, and hands over the configuration. It is covered by a monthly subscription with thirty days' notice and full export.
What does it cost?
A monthly subscription set by a written statement of work, because document volume, user count and integrations differ. The discovery call gives you a realistic range before you commit, and a demonstration against a sample of your own documents is part of the decision.
Which cloud and which models?
The cloud account your business already runs or prefers. Models are used under enterprise terms that exclude training on your data. The architecture is platform neutral by design, so the choice follows your existing estate rather than ours.
Where this sits
Where every engagement starts: the five dimensions, the ranked list and the baseline.
SEE THE ASSESSMENTInvoices read, matched, coded and staged for one-pass approval inside your accounting system.
SEE THE PACKAGEReadiness Bridge, Productivity Implementation, Operations Sprint and Custom AI.
SEE THE PATHTell us what your team keeps asking.
Four fields. We reply within one business day with whether the assistant fits and what a demonstration against a sample of your documents would involve. No pricing until the scope is written down.