IT Dynamic Systems GmbH

ARTICLY creates first-class audio experiences. ARTICLY is an AI audio startup that automatically transforms content from texts into high-quality audio formats such as podcasts and briefings. Companies, media companies and mobility providers reach their target audiences efficiently, personalized and without additional production effort. ARTICLY is an innovative platform for automated audio production that enables companies, publishers and platform operators to convert existing content such as articles, newsletters or RSS feeds into professional audio formats. Using cutting-edge artificial intelligence, high-quality podcasts, personalized news briefings and scalable audio offerings are created that are ideal for websites, apps, in-car entertainment, inflight systems or internal communications. ARTICLY combines text-to-speech technology with intelligent workflows, editorial logic and seamless integration into existing systems to significantly increase reach, user engagement and monetization potential. Companies benefit from efficient content repurposing, improved accessibility and a modern audio experience that optimally serves the growing consumption of podcasts and spoken content.

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.

cocoduro

cocoduro is building the agentic commerce layer for European grocery. Our AI shopping assistant learns what your household actually eats and buys, builds the basket for you, and finds the best price across retailers, so grocery shopping stops being a chore and starts running on autopilot.