Enterprise AI for IT leaders

Move AI from experiments into business use

A first AI experiment is quick to set up. Production use takes more: up-to-date company data, shared business concepts, managed permissions, and calculations that processes can rely on.

Qaicu brings these together in one service. Your existing systems can carry on as before, and you can use their information through a shared data layer.

When the next team or agent needs the same information, the work already done is there to reuse.

A shared service reduces shadow AI too. If staff have no managed way to use AI, company information ends up in general-purpose AI services that IT cannot see. Banning them does not remove the need, and team-specific tools scatter information, responsibilities and permissions.

Qaicu gives staff answers from the company’s own information, in a service IT has approved. Then they have less need to move information into other tools. IT keeps control of permissions and restrictions on information.

Qaicu Core is an AI-optimised data layer. It brings information from your company’s systems and documents together into one governed information base.

Core stores, versions and standardises information, and maps the relationships between business concepts. Take a customer in the CRM, the terms of a contract, a project’s costs and invoicing from the accounting system. Core can link them in the same business context.

An agent gets the information its task needs. It does not have to interpret the structure of every source system itself.

The shared information base serves Qaicu’s working environment, its ready-made agents and your company’s own AI solutions.

When an agent needs a margin, a balance or a cost comparison, Qaicu Core calculates it with defined calculation rules. The language model gets the finished result and the supporting information it needs to interpret it.

This keeps repeatable calculation separate from the analysis a language model produces. Whether the calculations are right depends on the source data and the calculation rules.

Calculating in Core can also mean sending fewer large batches of transactions to the language model. Core filters, aggregates and calculates before the model call, which cuts unnecessary token usage.

Core calculates. The language model interprets.

Company context guides interpretation. Permissions limit access to information.

A company’s data takes its meaning from its business. Qaicu holds a description of your company’s business model, ways of working, strategy and goals. The AI can then interpret information in that context.

A user’s role helps surface the views and content relevant to their work. Permissions work separately: they decide which information the user or agent may handle.

Core filters information by permissions before passing it to the language model. Qaicu does not rely on instructions written into the conversation to enforce permissions.

Information you share with Qaicu is processed and stored in Europe. It does not end up in language model training data. You can read about the security controls and practices in the Trust Center.

For example, the first implementation could be:

• A finance review agent that supports period-end close checks and variance investigation.
• A sales preparation agent that brings together customer information and previous conversations ahead of a meeting.
• Project tracking that combines the budget, actual costs and invoicing.

Once the first implementations have proved their value, the same foundation extends to new processes, user groups and agents.