Skip to content

Custom AI applications

Purpose-built applications centered on an AI task such as reading documents, extracting and checking information, classifying requests or supporting a specialist decision. We build the interface, the logic, the data connections and the deployment.

Discuss your projectScoped to your project

When you need this

  • People spend hours reading, copying or checking information from documents.
  • A specialist decision needs more consistent support, with a person still in control.
  • A prototype worked and now needs to become a real application.
  • Off-the-shelf tools do not fit your documents or your process.

How we do it

  1. 1. Define the workflow

    Who uses it, what goes in, what comes out, and where a person reviews or approves the result.

  2. 2. Engineer the AI layer

    Model choice, prompts, structured outputs and retrieval, measured against your test set as it is built.

  3. 3. Build the application

    Interface, permissions, integrations with your systems, logging and monitoring.

  4. 4. Accept and hand over

    Your acceptance review against agreed criteria, deployment, documentation and training.

What you get

  • A deployed application with interface and permissions
  • Integrations with your existing systems
  • Test set and evaluation results
  • Monitoring, logging and operating documentation
Example
Illustrative

An estimating team receives long construction document packages. The application reads each package, organizes the requirements that affect the estimate and links every item to its page. Estimators review and correct the list; final estimates stay with them.

Start with a project conversation

Scoped to your project

Tell us what you want to build. We reply to set up a short conversation. A clear project can be scoped directly; if the solution is not yet clear, solution design comes first.

Discuss your project

Questions

Which AI models do you use?

Whichever fits the task, cost and data requirements: managed APIs from the major providers, or privately hosted open models. The choice is made per project.

Who owns the code?

Ownership is agreed in writing before the build starts, including any existing Cennix components that are licensed rather than transferred.

Often combined with