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DataObrii highlights that Microsoft Research's new open-source framework Orchard addresses the problem of agents being trained in simplified environments and deployed inside complex systems.

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Research & Knowledge

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Microsoft Research’s new open-source framework, Orchard, addresses a problem that is easy to underestimate: agents are often trained in simplified environments and then deployed inside much more complex systems.

Oleksii Romanko|DataObrii team

Company

DataObrii

AI & Data Science R&D: Agentic Systems, Predictive & Pricing Models, and Production-Grade Data Pipelines.

Location
London, GB
Company size
16 employees

Building AI is easy. Making it work in production, scale with the business, and actually pay for itself? That’s the hard part. DataObrii is an R&D company specializing in complex AI, machine learning, and data systems. Led by a PhD from King’s College London, we combine mathematical research with production-grade engineering to design and build systems that are robust, scalable, and ready for real-world use. Core Expertise: Scalable Modeling: Demand forecasting and pricing models built for production. Agentic Systems: Autonomous AI agents and text processing systems and pipelines. Predictive ML: Predictive modeling, deep learning, and reinforcement learning. Data Foundations: Data pipelines, warehouse architecture, and feature engineering. Sector Expertise: Specialized AI and data R&D for Insurtech, Fintech, and Healthtech. Our work spans the full R&D cycle, from research and architecture to implementation and production, with a focus on technically demanding problems where standard approaches fall short. Working on a complex AI or data initiative? Let’s chat.

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DataObrii highlights that Microsoft Research's new open-source framework Orchard addresses the problem of agents being trained in simplified environments and deployed inside complex systems. | SeedOps