We bring AI
to business.
In the cloud and on-prem.

The scope determines the cost. We consider the workflow, data preparation, integrations, deployment environment and support requirements. After the initial audit, you receive a proposal with the work included, an estimated schedule and the commercial terms for your project. The initial audit is free and carries no obligation.

We compare both options against your workload and data handling requirements. A managed cloud service can reduce infrastructure work, while private deployment gives your team more control over the operating environment. The comparison includes model quality, expected use, infrastructure, support and the data connections involved. The recommendation follows your requirements and the evaluation results.

That is something we test on your actual tasks. We compare suitable models using representative documents, questions and expected outputs. The result depends on the task, language, model and application design. If different workflows need different models, we can propose a mixed architecture, with external processing limited to the uses you approve.

We agree on where data can be processed, who can access it and what the application may retain before connecting sources. The architecture covers documents, model requests, search indexes, logs and backups. Private deployment is available when the application needs to run in your environment. Access controls and testing remain part of the project in either deployment model; hosting location alone does not guarantee security or compliance.

We handle the agreed software work, including architecture, model configuration, search, application development, integrations and support. Your team provides the required data access, business expertise and a prepared deployment environment. If hardware is needed, you purchase it and arrange physical installation and warranty service through your chosen supplier. Responsibilities and prerequisites are documented in the project scope.

We can provide ongoing support under an agreed service level. This covers the defined application components, monitoring, evaluated updates, backups and incident response. The agreement specifies coverage and responsibilities, including dependencies on your infrastructure team or cloud provider. We also use operational feedback to propose improvements and additional workflows.

Yes. We can start with one team, one workflow and a defined set of data. Before building, we agree on what a useful result looks like and how to evaluate it. The pilot helps you decide whether to proceed, revise the approach or stop. Expansion can then add more users, sources or integrations based on what the first project demonstrates.