INXM, a Berlin-based startup developing an AI Process Execution Engine for enterprise operations, has raised €5.7 million in a pre-seed funding round led by Cherry Ventures and Redstone, with participation from Angel Invest, Linden Capital, and other investors. The funding will support initial enterprise deployments and further development of its automation platform.
Solving Enterprise AI Reliability Challenges
Many AI solutions struggle in enterprise environments due to unpredictable outputs, compliance concerns, and complex operational workflows. INXM addresses these challenges through its Process Execution Engine, designed to automate business processes with repeatable and auditable results.
"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." - Alex Oelling, CEO of INXM
Compiled AI Architecture
The platform is built on a concept called Compiled AI, which uses AI to design and optimize business processes while executing them through deterministic workflows. This approach combines AI flexibility with the reliability, traceability, and control required by enterprise and compliance teams.
"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." - Matthias Kainer, CTO of INXM
Expansion Plans
Rather than replacing existing systems, INXM integrates with enterprise software stacks to automate operations within months. The company plans to focus on industrial enterprises, where process complexity, regulatory requirements, and limited engineering resources often slow AI adoption. The platform is designed for European businesses, offering local deployment and full data ownership to meet governance and compliance standards.