Document processing
Extract, check and classify information, transfer approved results into target systems and route exceptions to people. Define which documents and decisions require review before automating them.
AI Integration for SMEs
AI that works with your documents, systems and business processes.
You do not need an AI prototype to start. Bring a recurring task, a document bottleneck or a knowledge-access problem. We first assess whether an existing product or conventional automation would solve it more simply.
Discuss a workflow to automateInternal knowledge access
Answers grounded in approved information, with source references and appropriate permissions. Test unanswered questions, conflicting sources and access boundaries rather than expecting universal accuracy.
Workflow assistance
Request routing, draft preparation, business-system integration and approval steps. Design recoverable failures and a clear path for a person to intervene.
- Assess the workflow
- Choose an appropriate solution
- Evaluate representative tasks
- Integrate
- Train users
- Agree support where needed
Examples of scoped deliverables
- Workflow assessment and build/buy/automation recommendation
- Integrated document, knowledge or workflow solution
- Representative evaluation tasks and documented limitations
- User guidance, handover and separately agreed maintenance
Cloud, private-cloud and on-premises deployments are selected against data, integration and operating requirements. Optional software maintenance is distinct from managed hosting and continuous operations, which are not included in the current offer.
Possible acceptance measures include processing time, correction rate, task completion, cost per item and exception handling. Establish baselines and targets within the project; these are not achieved savings claims.
Before we start
Do we need to build our own AI system?
No. We consider existing products and conventional automation before proposing bespoke AI.
What happens to sensitive information?
Agree approved sources, access permissions, model/provider choices, data locations and human review. Controls depend on the workflow; there is no blanket compliance or accuracy guarantee.
What happens after delivery?
Users receive guidance and agreed handover. Optional maintenance scope and response arrangements can be agreed separately; continuous operations and managed hosting are not assumed.
Case Studies
Selected engineering projects
Anonymized project experience in Financial Services, Life Sciences and self-hosted AI automation, with concrete approaches, results and lessons learned.
Independent technology consulting
Client automation · outcomes not yet measured
Automated Project Matching for an Independent Consultant
A self-hosted Python agent compares German and English freelance listings against multiple CVs and groups relevant opportunities into email digests. Time savings and match precision have not yet been measured.
Read the case studyThe consultant project is delivered local-AI workflow automation. Match precision, time savings and commercial outcomes remain unmeasured. AI-assisted coding in the separate audit-trail project is not presented as an AI integration reference.
Contact
Discuss a workflow to automate
Tell us what you need to analyse, build or maintain. We will clarify the scope and suggest an appropriate next step.