Sparkasse Leasing
LeasingApp brought offer preparation, role-specific work and document handling into an on-premise application. Offer generation moved from days to minutes.
AI Enablement & Automation
Put AI to work across your business.
Connect your systems and data with AI agents that support decisions and automate workflows—with clear controls and human oversight.
Choose where AI can make a useful difference
People copy the same information between applications. A report depends on several spreadsheets. A customer waits while a team assembles an offer. An automated step fails and nobody knows who should act.
We map the process, connect the systems and make the handoffs explicit. AI can support classification, information retrieval or document work where it fits the task. Rules and conventional software remain useful wherever the process needs predictable behaviour.
From business priority to working implementation
- 01Choose a valuable first use case.
- Identify a reporting need, repeated task or decision that better access to information could improve. Agree what a useful result looks like.
- 02Connect the systems and data.
- Establish source quality, access permissions and integration requirements around the workflow.
- 03Implement agents and automation.
- Build the analysis, reporting or process functionality, with clear boundaries for automated actions and human review.
- 04Evaluate and operate.
- Test outputs against representative tasks, agree ownership and monitoring, and use the results to decide what to extend next.
Integration and automation scope
- Application and API integrations with clear ownership of data and failures.
- Document and approval workflows with appropriate permissions and audit trails.
- Data pipelines and reporting interfaces that reduce repeated handling.
- Onboarding and internal knowledge flows connected to how teams work.
- Monitoring and exception handling so the process can be operated after launch.
AI agents in an international group
For an international group of approximately 30 companies, a multi-agent solution reads from several systems to support financial and operational analysis, deviations from plan, market projections and recommendations. Reports are drafted for human review and sending. The implementation combines data access controls, checks on calculations and responses, testing and human responsibility.
Automation experience from financial operations
S-Premium
A separate insurance-offer platform connected the work of S-Premium, leasing stakeholders and insurance brokers. It also moved offer generation from days to minutes.
Each project was delivered in under four months and has continued through three years of updates, maintenance and development. Each has its own client organisation and project owner.
For institutional reporting, WMP brings continuous data entry and automated reporting into a shared workflow across government bodies.
Questions
- Do we need an AI prototype before contacting you?
- No. Start with the workflow you want to improve. We can define the process, data requirements and first implementation scope before a prototype exists.
- Can the solution connect to our current applications?
- Integration is part of the service. We first examine the systems, available interfaces, access requirements and ownership of the data involved.
Start with one workflow and a clear investment decision
Bring the reporting need, repeated task or business question you want to address. We review the existing systems, data quality, access requirements and process ownership before proposing the first implementation.
Agree how to assess the result: time spent, manual steps, output quality or access to useful information. The proposal defines scope, client dependencies, timing, cost and responsibility for operation. Where a pilot is useful, its findings guide the decision to extend the solution.