Startup Collaboration with MAHLE – Boost digital customer services & internal process efficiency

What is MAHLE looking for? 

MAHLE is looking for advanced, market-ready AI automation solutions to simplify and accelerate the automation of indirect business processes—without the need for rigid, predefined workflows or deep technical integration. The ideal solution should be able to handle both structured and unstructured inputs (such as emails, PDFs, or varied document formats) and adapt dynamically to changes in process logic or input structure with minimal manual effort.

While MAHLE has extensive experience with traditional RPA tools, their limitations—especially around flexibility and maintenance—are becoming increasingly apparent in dynamic business environments. As part of a structured proof-of-concept and pilot phase, MAHLE seeks solutions that can be implemented quickly, require little effort from internal departments, and demonstrate clear potential for long-term scalability across departments.

Core Question 

How can we automate indirect business processes in a way that is fast, flexible, and resilient to change—without relying on rigid process structures or extensive integration efforts?

Goals & Criteria 

The solution should ideally…

• Reduced setup time compared to existing RPA workflows (e.g. from several days to a few hours)
• Lower coordination effort between IT and business departments during implementation
• Enable end-to-end automation of indirect business processes — including those triggered by unstructured or semi-structured inputs (e.g. free-text emails, scanned documents, or inconsistent file formats).
• Be resilient to changes in document layouts, data formats, languages, or business logic — without requiring major rework or developer support.
• Allow for quick implementation within a few days, with minimal effort from internal departments (plug-and-play or low-code/no-code preferred).
• Be a mature, product-based solution — no custom development tools or consulting-only offers.
• Support use cases across various functions (e.g. finance, procurement, HR, shared services).
• Be compatible with MAHLE’s system landscape, including SAP (S/4HANA) and Microsoft 365 environments.
• Offer a secure, GDPR-compliant, cloud-based architecture, and be ready for structured pilot implementation

In Scope

This project is focused on identifying and testing next-generation AI-based automation solutions that go significantly beyond the limitations of traditional RPA tools.

Specifically, we are looking to explore:

• Indirect Business processes that are currently manual, repetitive, and triggered by loosely structured data (e.g. email-driven requests, free-text documents, non-standard formats). Typical input types include free-text emails, variably formatted invoices (including in multiple languages), and project-related cost entries
• Use cases across departments (e.g. finance, procurement, shared services) where automation can replace or support human intervention and reduce effort, errors, and complexity.
• Next-generation intelligent automation technologies that overcome the rigidity of current RPA systems — especially solutions that are robust against changing process structures, document layouts, and language variations.
• Pilots where your solution can be tested in a real-world environment, using representative data and process scenarios from MAHLE’s SAP (S/4HANA) and Microsoft 365 infrastructure.
• Flexible, AI-enhanced process automation that reduces implementation time and human configuration effort — ideally with a modular or plug-and-play setup.

Out of Scope

The following approaches are not suitable for this project and will not be considered:

• Micro-processes or task automation without meaningful business value (e.g. generic task managers or checklist tools)
• Traditional RPA solutions that rely on static process logic, fixed input formats, or high manual maintenance — these have already been extensively tested and are not scalable within MAHLE’s dynamic environment.
• Solutions that require custom development or lengthy configuration phases before going live.
• Tools that depend on new API integrations into core systems (due to security and resource constraints).
• Hardware automation or physical robotics.
• Consulting-only offers, or MVP-stage tools without proven readiness or enterprise references.
• Low-impact task automation tools that lack scalability.

What should your application communicate? 

• A concise description of your solution, including its core automation capabilities and how it handles unstructured or dynamic inputs.
• An explanation of how your solution works technically (e.g. input handling, AI capabilities, system compatibility, interface design).
• Details on how the solution can be implemented quickly and what resources (if any) are needed from MAHLE departments.
• Reference projects or customers, ideally from the industrial or enterprise sector.
• A proposed pilot scenario: including timeline, expected process gains, and relevant KPIs (e.g. time savings, reduction of manual effort).
• A summary of your technical and legal readiness: GDPR compliance, data security standards, ability to work under NDA, etc.
• Your pricing model and how it compares to the potential process savings and efficiency improvements.

Who are we looking for?

We are looking for innovative partners who:

• Offer a product-based, automation-first solution (no MVPs or custom service tools).
• Have at least one paying customer and proven use cases — ideally in enterprise or industrial environments.
• Can demonstrate quick implementation capability with minimal onboarding effort on the client side.
• Are able to operate under German/EU legal and data protection standards (e.g. NDA, DPA, GDPR, EU AI Act).
• Use AI-driven approaches to handle variability in documents, inputs, or processes.
• Are open to co-developing and evolving their solution based on real use cases and feedback.
• Can support a structured proof of concept and are willing to scale within a venture client partnership.
• Are comfortable working in English