We develop custom AI applications for businesses – from intelligent document processing and knowledge assistants to automated request handling. Our solutions integrate with existing systems and support reliable business workflows.
Discuss an AI use case
Typical challenges we can explore for your business.
Incoming documents often contain information that employees currently transfer manually. An AI application can suggest relevant fields and flag uncertain results for professional review. We evaluate which document types are suitable using representative examples.
Instructions and specialist information are often spread across multiple files. An AI knowledge assistant can prepare answers based on approved sources and reference the relevant information. Access permissions and keeping content up to date are essential parts of the solution.
Recurring messages need to be classified and prepared for further processing. AI can suggest categories, summaries, or draft responses. Important decisions remain subject to review and approval by qualified employees.
Artificial intelligence delivers practical value when it supports a specific business task. A general desire for greater efficiency is not yet a sufficient project goal. Together, we identify the available inputs, the expected results, and the criteria for measuring improvement.
We also evaluate whether rule-based automation or conventional software would be a better fit. Not every workflow requires a large language model (LLM). However, AI can be a valuable addition when dealing with unstructured text, documents, or varying language and formats.
We recommend starting with a clearly defined task and representative examples. Before development begins, we agree on evaluation criteria: What makes a result acceptable from a business perspective? Which errors are critical? How much additional human review will your team need?
An AI pilot helps answer these questions through practical testing. It can demonstrate the achievable quality and reveal where data, processes, or the technical approach need adjustment.
The use cases described here represent potential project approaches, not claimed customer results or ready-made standard features.
A production-ready AI solution involves more than calling an AI model. It requires appropriate data sources, access permissions, a suitable user interface, and reliable error handling.
Through APIs, AI capabilities can be integrated into existing business applications, allowing employees to work with familiar tools instead of switching between additional platforms.
For document-based answers, approved information can first be retrieved and then provided to the AI model as relevant context. This approach can support more grounded responses, but the model does not replace access controls or professional review.
Learn more about our approach to AI Integration.
Before implementation, we clarify the types of data involved, how information will be processed, which providers may be used, and where the solution will operate.
Confidential information should only be processed within the systems and environments approved for the specific project. We coordinate data protection requirements and internal approvals with the responsible stakeholders in your organization.
For production use, we also consider cost controls, response times, monitoring, and fallback procedures.
When models, data sources, or business requirements change, important test cases need to be evaluated again.
Human approval is particularly important when AI-generated results affect business records or binding decisions.
Our technical background includes custom enterprise software development and system integration.
With James, our AI Phone Assistant, we have also developed our own AI-powered product.
We assess separately which existing product capabilities may fit your requirements and where custom AI development is the more appropriate solution.
Our guide to AI for Small and Medium-Sized Businesses provides additional ideas.
If your main challenge involves reliable data exchange between business systems, Business Process Automation may be a more suitable starting point.
Improve an existing application, build something new or simplify processes with AI? Tell us about it.
