VY.EcoSys is a platform focused on enabling secure, personalized recommendations and news streams for SME-to-SME (Small and Medium Enterprise) cooperation without forcing participants to divulge sensitive business data to each other.
Core Technology and Approach
– VY.EcoSys offers on-device data storage and AI analytics, allowing SMEs to analyze their own data locally using specialized AI models, mini-SmallTradeModels (mini-STMs); based on the outcome of the data-analytics, the mini-STM will then generate product recommendations locally.
– These recommendations can as well be shared with other SMEs via the Personalized News Stream; shared recommendations are the indication of demand only or offers—not the raw SME-data itself. The deal is made by accepting the offer.
– This mechanism working for the generation and sharing of recommendations works for recommending and sharing professional expert content as well via the Personalized News Stream. Market information and innovation will travel fast.
– VY.EcoSys supports decentralized, privacy-focused collaboration in SME component industries such as automotive parts, construction, and hospitality as well.
Data Privacy and Trusted Third Parties (TTPs)
– SMEs can engage their own Trusted Third Parties (TTPs) to analyze their data using VY.EcoSys, ensuring privacy and control comparable to legal or medical professions.
– TTPs use industry-specific, fine-tuned AI models to transform private SME data into actionable recommendations, further enhancing privacy and tailored business intelligence.
Commercial Model and Ecosystem Applications
– Recommendations and deals facilitated by VY.EcoSys are monetized (e.g., a small transaction fee paid by vendors), optionally utilizing Instant Payments by integrated embedded banking.
– Earned credits (“Rec-Dollars”) can be used by SMEs to access professional expert content and resources within the ecosystem.
VY.EcoSys is designed to help SMEs in component industries safely cooperate, predict demand and supply trends, and order the needed components, all while keeping their sensitive data private and on-device.