The numbers tell a story that manufacturing executives will recognize: 95 hours of engineering time consumed per request for quote, technical proposals that take weeks to assemble, and sales teams drowning in feasibility checks and product configurations. Munich-based Atira said Tuesday it has raised $17.5 million to solve that problem with AI agents designed specifically for the industrial sector.
The financing includes a $15 million seed round led by Accel and a previously undisclosed $2.5 million pre-seed investment. Atira's software acts as what the company calls an "AI orchestration layer" positioned between customer relationship management and enterprise resource planning systems, automating the technical sales workflows that have largely resisted digitization in manufacturing.
Florian Diegruber, Atira's co-founder and CEO, framed the opportunity in stark terms. "Sales engineering is one of the largest workflows in manufacturing that software has never truly automated," he told Fortune, which first reported the funding. Accel and Atira estimate the work that happens between CRM and ERP systems represents more than $128 billion in annual labor spend globally.
Diegruber previously led commercial accounts at Palantir in the DACH region, experience that appears to have shaped his view of where AI could make an immediate impact. His co-founder, August DuMont Schütte, worked as a software and machine learning engineer at Google after studying at ETH Zürich.
The platform they built extracts requirements from inbound requests for quotes and tenders, runs feasibility analyses, configures products, generates pricing and drafts technical documentation before pushing results back into existing enterprise systems. Atira claims customers are cutting their ask-to-bid times by up to 80 percent. German railway equipment maker ROBEL Railway Construction, for instance, says it has reclaimed those 95 hours of engineering time per RFQ using the system.
That kind of efficiency gain has attracted a client roster that reads like a who's who of German industrial machinery. ABB E-Mobility deployed Atira globally. CHIRON Group, the precision machine tool manufacturer, runs the platform across more than 70 users and is expanding into the United States. Rubber products giant Rema Tip Top uses it across operations in Australia, Brazil and Chile. Theegarten-Pactec and Fette Compacting have also signed on.
Since launching commercially last November, Atira has brought roughly 15 customers into full production, with five deploying the software to more than 100 users each. The traction is notable for a startup that had just four employees at the beginning of last year. The team has since grown to about 15, with nine additional hires in the pipeline.
Diegruber said most of the new capital will flow into engineering and the startup's first non-founder commercial hires. UVC Partners, which joined the seed round alongside Fortino Ventures and Booom, outlined a broader agenda in a blog post: international expansion, product development and adjacent workflows including pricing intelligence, aftersales and supplier coordination. The investor group also includes angel backers Ann-Kristin Achleitner, Whirlpool chairman and CEO Marc Bitzer, Dr. Markus Flik and Celonis co-founder and co-CEO Bastian Nominacher.
Atira enters a market where competition is materializing fast. Salesforce and ServiceNow are embedding AI capabilities deeper into their sales platforms. Roadrunner, a startup rebuilding quote-to-cash processes, raised $27 million in combined seed and Series A funding led by Kleiner Perkins and Founders Fund in May. Threekit launched an AI sales agent for manufacturers in June that integrates with CPQ and ERP systems.
Atira declined to disclose its valuation. For now, the company appears focused on proving that the tedious, technical work between initial customer inquiry and final proposal can be compressed not just incrementally but by orders of magnitude. Whether that thesis holds across the broader manufacturing landscape will likely determine if Atira becomes a category leader or another well-funded experiment in applying AI to legacy workflows.
