Although we have more than 1 billion spreadsheet users worldwide, there is not a single proper go-to platform for sharing spreadsheet templates based on category. We have Spotify for music, Airbnb for accommodation, etc, and now Excelarete for spreadsheets, especially for business-related templates. Additionally, we allow business experts network and promote themselves via selling their expertise in industry-specific spreadsheet formats.

Der Online-Modehandel leidet unter einer sehr hohen Retourenquote: In Deutschland werden über 50 % aller online bestellten Modeartikel zurückgesendet. Dies verursacht hohe Kosten für Händler sowie erhebliche CO₂-Emissionen. Gleichzeitig sind Kundinnen und Kunden unzufrieden, da sie Kleidung vor dem Kauf nicht anprobieren können und häufig mehrere Größen bestellen. GO TRY ON schließt diese Lücke, indem es den Online-Shop mit der Umkleidekabine im Geschäft verbindet. Kundinnen und Kunden reservieren Artikel online, buchen einen Anprobetermin im Geschäft und bezahlen nur die Produkte, die sie behalten. Dadurch werden Retouren vermieden, das Einkaufserlebnis verbessert und Kosten sowie Umweltbelastungen reduziert. Die Lösung lässt sich einfach über ein Buchungs-Widget in bestehende Online-Shops integrieren, ohne zusätzliche Infrastruktur.

A scalable PV Scanner that can be employed by small contractors as well as large scale solar farms. It captures high resolution imagery not offered by the competition and relies on readily available, cheap components.

Karthik is a Data Scientist and Machine Learning Engineer with extensive experience in developing practical AI solutions that create sustainable business value. He has expertise in Machine Learning, Deep Learning, Computer Vision, NLP, Generative AI, as well as recommendation systems and cloud-based data platforms. His focus is on developing scalable end-to-end AI applications – from data acquisition through modeling and deployment to monitoring production systems. He is proficient in MLOps technologies, CI/CD, Docker, Kubernetes, MLflow, as well as AWS and Azure, and possesses in-depth knowledge of Python, SQL, data engineering, and ETL processes. Karthik has worked in research, corporate, and production environments, processed complex datasets, and developed scalable machine learning systems for thousands of users. He particularly values collaboration in innovative teams and the dynamics of startup environments.

A mesh network is a combination of electronic devices – also called nodes – that form branches to other nodes with each other. This allows messages to be forwarded from node to node (hops), enabling comprehensive communication without mobile radio or WIFI. In radio mesh networks, there are numerous parameters that influence the performance of the network. That's why we developed OMNIHOP. An algorithm that independently optimizes the transmission parameters of radio communication in mesh networks so that maximum range with maximum data throughput and best battery life is always achieved. This allows, for example, rescue workers in disaster areas, where no communication infrastructure is available, to set up their own comprehensive communication system within minutes.

Current smart home assistants are often built around complex big tech ecosystems, creating high entry barriers and privacy concerns for older generations. Our solution solves this problem by introducing a plug and play, voice controlled AI companion created exclusively for seniors. Connected easily to any television, the system allows users to navigate the digital world naturally. It assists with vital everyday tasks like online shopping, bank transfers, and calendar management, while also providing social features like video chatting and community gaming to prevent isolation. The technical breakthrough of our prototype is its completely decentralized approach. By utilizing a local AI, the system processes everything directly on the device itself. This guarantees maximum security and strict GDPR compliance without relying on remote cloud networks. The initial prototype is fully operational and ready for pilot testing within the Saxon innovation network.

As an ambitious food scientist, I am particularly enthusiastic about the transfer of innovative research results into marketable products and economic applications. My competencies include laboratory analytics, product and recipe development, process optimization, as well as quality management and quality control according to HACCP and ISO standards. German Research Experience: Two years of work as a visiting scientist at the Mittweida University of Applied Sciences. UNIDO Expertise: Specialization in Organic Production, certified by the United Nations Industrial Development Organization (UNIDO, 2026). Practical Laboratory Analytics: Sound experience in applying physical-chemical and rheological investigation methods for quality assessment and product development in the field of FoodTech and Research & Development (R&D)

Rivo Meals is the digital B2B canteen for modern companies, not a delivery app but a workplace benefit: one platform giving any employer a fresh daily lunch their team looks forward to, funded tax-free with zero admin. We onboard the company and team, and employees order from their profile by 09:00. Our engine turns every order into one kitchen ticket and a single delivery per office, so meals arrive together at noon in reusable bowls. Staff pay €0 at base, up to €2.50 for premium. The problem is bigger than food: in a hybrid world, companies struggle to fill offices, build culture, and keep talent. Canteens cost €200k+ a year, delivery apps leave no shared table, and a pay rise is taxed twice. The Sachbezug allowance (§8/§40 EStG), up to €7.50/day tax-free, goes unclaimed as it is too complex to run. Rivo makes lunch a benefit that retains people and builds culture. The subsidy applies at source, billing is one monthly invoice, and a dashboard tracks participation, spend, and usage.

You have production residues containing low concentrated critical raw metals, like Ga, Ger or In? We are happy to take your residues as a feed and to recover the raw materials in it. Let's get in touch!

Recycled carbon fiber (rCF) has been discussed for years as a material with considerable ecological and economic potential - however, industrial penetration remains significantly below expectations. We assume that this is not a material problem, but a structural development problem at the interface between fiber processing, semi-finished product manufacturing, and industrial applicability. POLYVEX addresses precisely this interface with a data-driven, B2B-oriented approach. The goal is to make rCF-based nonwoven semi-finished products usable for industrial end-users, thereby closing a gap that has existed for years between the state of research and industrial application. The project is being developed from the Saxon university and research environment, is in the preparation phase for the EXIST start-up grant, and is designed for a multi-year, capital-intensive development phase with a clear industrial application perspective.

Ziel ist die Entwicklung einer modularen, universellen und durch NutzerInnen definierbaren Fernbedienung, welche im Vergleich zu handelsüblichen Fernbedienungen u.a. austauschbare und größere Tasten hat, und sich mit mehreren verschiedenen Geräten im Haushalt/der Umgebung verbinden lässt. Dies soll vor allem für die, die sich auf ein intuitives, haptisches Interface verlassen, als Alternative zu mehreren oder sogar digitalen Fernbedienungen dienen.