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Rimes launches AI-enabled investment data platform

By Milan Rojan

Today

  • Agentic AI
  • AI
  • Artificial Intelligence
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Rimes has launched a new investment data and intelligence platform designed to help asset owners, asset managers and asset servicers streamline investment workflows and expand the use of artificial intelligence across capital markets.

The Intelligence Fabric for Capital Markets has brought together Rimes’ enterprise data management and investment intelligence capabilities into a unified architecture. The platform has been designed to provide connected investment data, decision-focused workflows and operational controls for institutional investors.

Vijay Mayadas, President and CEO of Rimes, has said investment firms have invested significantly in data capabilities, but the infrastructure required to act on that data has not kept pace with AI-driven investment management.

Rimes has said its data network connects more than 1,000 data partners, thousands of datasets and billions of data points daily. The network has supported more than 400 institutional clients with investment data and intelligence.

The launch has addressed challenges around fragmented data environments, as investment firms have continued to manage information across multiple providers, platforms and business functions. Rimes has said the increasing use of AI in investment processes has also created greater requirements for data lineage, explainability and operational control.

The platform has been structured around four areas: a trusted data network, connected enterprise intelligence, decision-grade workflows and continuous operational control. These capabilities have been designed to provide portfolio managers, risk teams, operations and AI systems with a common data foundation.

Rimes has positioned the platform as a foundation for more automated investment workflows as AI has moved from supporting investment decisions towards executing tasks. The company has said the architecture will enable institutional investors to scale AI-enabled processes while maintaining greater control over the underlying investment data and workflows.

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