Munich Startup
Floy GmbH

Floy GmbH

Floy develops AI-powered software that assists radiologists in detecting complex and hard-to-identify diseases. The collaboration between AI and radiologists ensures optimal patient outcomes by enabling early detection and thus ea...

Founded2021
Business ModelB2B
IndustryIT/Technology
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About Floy GmbH

Floy develops AI-powered software that assists radiologists in detecting complex and hard-to-identify diseases. The collaboration between AI and radiologists ensures optimal patient outcomes by enabling early detection and thus early treatment of diseases. One of the distinguishing features is the innovative incentive structure. Floy cooperates with radiology practices to jointly offer patients AI as a “second read.” This unique approach motivates radiologists to use Floy AI and promotes broad adoption. Since its founding in 2021, Floy has raised €3.4 million in funding and rapidly expanded its presence to over 100 radiology practices to date. The overarching goal is to assume a pioneering role in proactive medicine by providing exceptional AI-powered diagnostic experiences for health-conscious patients.

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CarbonInsights

CarbonInsights

The challenge many companies face in managing CO₂ emissions lies less in a lack of willingness to reduce them, but rather in the reliable capture and structuring of relevant data. The central bottleneck in today’s carbon accounting is not the calculation itself, but the availability and preparation of emissions-related information. Existing solutions often require extensive manual data entry, rely on complex enterprise systems, or are economically inaccessible for small and medium-sized businesses. At the same time, the majority of emissions originate in supply chains and operational processes that are documented but not systematically analyzed. The CarbonInsights system addresses this exact point by fundamentally shifting the entry point for CO₂ accounting. Rather than requiring companies to manually collect data, the system uses existing business documents as the primary data source. Invoices, delivery notes, and energy bills are processed automatically, allowing emissions-relevant activities to be extracted directly from real operational data. The system architecture combines document processing, structured data extraction, and automated classification. Artificial intelligence is strategically applied to interpret unstructured content, while the actual emissions calculation remains rule-based and transparent. This separation enables both scalability and transparency of results. The result is a structured CO₂ balance, organized by categories such as transport, energy, and materials. Beyond mere reporting, the system establishes a direct connection between emissions and the underlying operational structures. Based on this, prioritized optimization measures are derived that are tailored to the specific business model and identified emissions focus areas. This approach transforms CO₂ accounting from a purely retrospective reporting obligation into a forward-looking analytical tool. By integrating into existing document flows, the CarbonInsights system significantly reduces manual effort and makes sound emissions analysis accessible even for companies without specialized sustainability infrastructure. In a regulatory environment where emissions transparency is increasingly mandatory, this approach offers a practical way to gain reliable insights into your own CO₂ footprint and derive concrete measures for emissions reduction.

B2BIT/Technology

2026Founded
1-10Team size
Seed stage