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Heissenberger Laboratory

Service

AI Agents & Process Automation

Identify recurring workflows, integrate AI agents into your existing systems and make the benefit measurable – with clear rules for when a human decides.

AI agents are software that plans and carries out tasks on its own: they read documents and emails, look up information in your systems, prepare decisions and trigger the next steps. Used well, they take over routine work – and your people gain time for what really needs experience.

An AI agent is only as good as the process it is embedded in. That’s why I never start with the technology, but with your workflow and your goal. ‒ Andreas Heissenberger, Technology Mediator

Typical use cases:

  • Understanding, routing and pre-processing incoming requests, emails and documents
  • Reconciling data between systems that is still transferred by hand today
  • Preparing quotes, reports and summaries from existing information
  • Making knowledge from internal documents and systems accessible to staff and customers
  • Speeding up review and approval processes where a human makes the final decision

Approach

  1. Process analysis: Which workflows cost the most time today, where do errors occur, where does the data live? The result is a prioritised list with effort, benefit and risks.
  2. Pilot: One selected process is implemented with an AI agent and tested in day-to-day work with real cases. Metrics defined up front show whether it pays off.
  3. Integration: The agent is connected to your existing systems – CRM, ERP, email, document storage or custom interfaces.
  4. Operations and evolution: Ongoing monitoring of quality, cost and availability, regular reviews and step-by-step expansion to further processes.

Responsible use

AI agents make decisions with real consequences in your business. That’s why these points are part of the concept from day one:

  • Humans stay in control: Clear rules about which steps the agent handles on its own and where approval is required
  • Traceability: Every action of the agent is logged and can be reviewed afterwards
  • Data protection: Choice of models and hosting to match your GDPR and confidentiality requirements
  • Legal framework: Classification of the use case under the EU AI Act
  • Cost control: Transparent operating costs and usage monitoring

Services

  • Potential analysis: where do AI agents pay off in your business?
  • Concept and architecture of agent solutions
  • Selection of AI models and providers
  • Development and integration of AI agents into existing systems
  • Pilot projects with measurable success criteria
  • Operations, monitoring and evolution
  • Second opinion on existing AI projects and offers