OU.Chat.
Your enterprise AI. Your data. Your control.
OU.Chat: Your enterprise AI. Your data. Your control.
OU.Chat is the AI layer your organization owns outright. It is a white-label mobile app you hand to staff and customers, backed by AI that runs on your data and your rules. No prompt leaves for a public model. You build internal tools and customer-facing support that become a second brain for the company, and that brain stays yours after the contract ends.
The only AI here that never sends a single prompt to OpenAI or Google. The model runs on your data, inside your walls, under your brand.
- Enterprises that cannot send data to public AI providers
- Regulated teams that need sovereign, private AI
- Companies building internal AI tools they want to keep
Why it exists.
Every public AI tool asks you to ship your data to someone else's model to get an answer back. For a bank, a hospital, a government contractor, or any company with a real data-protection duty, that is a non-starter. So teams either ban AI and fall behind, or use it quietly and carry the risk. OU.Chat removes the trade. The intelligence comes to your data instead of your data going to the model.
The capabilities, plainly.
White-label mobile app
Ship an AI app under your own brand to staff and customers. They log in, and you decide what it is allowed to do.
Your models, privately hosted
Runs on open-weight or self-hosted models inside your boundary. No prompt or document is sent to OpenAI, Google, or any public provider.
A second brain for the org
Connect your documents, policies, and systems so the AI answers from what your company actually knows, for both internal and customer-facing use.
Build tools that stay
The workflows and tools you build live in your instance. They do not evaporate when a subscription lapses.
You control the experience
Roles, guardrails, tone, and what each audience can access are yours to set. Staff get one surface, customers get another.
What it changes, by the person who owns the number.
Your board wants the AI productivity story, but legal will not let customer data touch a US model. You have been stuck between the two for a year.
Ship AI across the company without a single record leaving your boundary. The AI advantage, with the compliance answer already written.
Support and ops paste the same policies into ChatGPT all day, off the books, because it is faster. You have no visibility into what leaves.
One sanctioned app on their phones, answering from your own playbooks. Faster work, and every query stays inside the house.
You want an AI concierge in your customer app, but you will not put your customer list or your brand voice into a third-party bot.
A branded AI assistant your customers log into, trained on your content, that never leaks a name or a message to a public model.
A private bank rolls out AI to 400 staff in six weeks.
The relationship managers get a branded app on their phones. They ask it about product terms, compliance limits, and a client's history, and it answers from the bank's own documents. The models run inside the bank's cloud, so nothing reaches an outside provider. Six months later the bank adds a customer-facing version for account holders. Same brain, different door, still nothing leaves the boundary.
- Self-hosted models
- White-label mobile
- Private RAG
- Role-based access
- Where do the models run?
- Inside your environment: your cloud, your VPC, or on-prem where required. Open-weight models are the default, so you are never dependent on one vendor's API or pricing.
- What happens if we stop paying?
- The tools and knowledge you built are yours. This is infrastructure you own, not a rented seat that goes dark when the invoice lapses.