INXM raises €5.7M to tackle enterprise AI execution challenges

INXM, a Berlin-based startup developing AI-powered process automation technology for enterprise and industrial operations, has raised €5.7 million in a pre-seed funding round as it emerges from stealth. The round was led by Cherry Ventures and Redstone, with participation from Angel Invest, Linden Capital and other business angels.

Many organisations continue to face challenges when deploying AI within operational workflows. While AI systems can generate useful outputs, they often lack the consistency, auditability and reliability required for business-critical processes, particularly in environments that depend on complex workflows, legacy software and strict compliance requirements.

INXM was founded by Alex Oelling, Matthias Kainer, Jesper Bylund and Kamil Klüber to address the gap between AI-generated insights and reliable operational execution. The founding team previously worked on enterprise systems in sectors including aerospace and deep technology, where they experienced the operational challenges associated with deploying AI in complex environments.

We founded INXM because we've seen first-hand how enterprise AI projects fail: years of implementation, armies of engineers, and AI systems that break more than they fix. Knowledge workers still copy-paste between ERP, PLM, Excel, email, and approval workflows to close a month.
We have set out to build AI that finishes the work for you. We’re building the system that turns AI from a productivity tool into the operational backbone of European industry and its processes,

said Alex Oelling, CEO of INXM.

The company has developed what it describes as a Process Execution Engine based on a concept it calls "Compiled AI." Rather than relying on large language models to interpret and execute every task in real time, the platform uses AI to design and refine operational workflows, which are then executed through deterministic processes intended to deliver repeatable and auditable outcomes.

The platform’s orchestration layer coordinates activities across enterprise systems, employees and workflows, enabling organisations to automate processes while maintaining greater predictability and oversight.

At its core, Compiled AI means you use LLMs to generate deterministic, enterprise-ready code. You then run the code to achieve your outcome. This gives you the flexibility of natural language from AI models, but the testability of deterministic code,

explained Matthias Kainer, CTO of INXM.

According to the company, the platform is designed to integrate with existing enterprise infrastructure rather than replace it, helping organisations automate processes without large-scale system overhauls. INXM says its approach is particularly suited to industrial operations, where process complexity, limited engineering resources and compliance requirements often make AI adoption more challenging.

Built and deployed in Europe, the platform is designed to support the data governance, compliance and deployment requirements of European enterprise customers.

The funding will support INXM’s initial enterprise deployments and the continued development of its platform, which is designed to automate and execute complex business processes across industrial and enterprise environments.