Arcana’s connector gives investment teams AI grounded in their portfolios, risk, performance, and proprietary research
Arcana, the portfolio intelligence platform built for hedge funds and asset managers, announced its availability in Claude’s official Connector Directory, giving institutional investment teams a new way to work with their portfolio intelligence directly in Claude.
“The real value of AI in investing comes when it understands the same context the investor does.”
Powered by Arcana’s Model Context Protocol (MCP) connector, the integration brings portfolio, risk, performance, and research data into Claude, enabling investment professionals to use natural language to ask questions about and analyze their portfolios, investment estimates, and research notes. This grounds Claude’s responses in the data and context that drive each team’s investment process.
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“The real value of AI in investing comes when it understands the same context the investor does: the portfolio, the risk, the performance, the research, and the decisions that came before,” said Rich Falk-Wallace, CEO and Co-Founder of Arcana. “Connecting Arcana with Claude means investors can ask the questions they actually care about and get answers grounded in the institutional data and analytics they already trust.”
For example, an investment professional could ask Claude to:
- Summarize the major sources of risk across a portfolio
- Identify changes in portfolio exposures
- Explain recent portfolio performance
- Understand thematics and crowding
- Compare current positioning with a benchmark
- Surface relevant research or investment notes
- Review price targets, conviction scores or other proprietary investment data
- Explore potential hedge ideas
The launch is part of Arcana’s broader strategy to make portfolio intelligence available wherever investment teams work. In addition to Arcana’s web, desktop, and iOS applications, clients can access Arcana through Excel, APIs, automated reporting, and AI interfaces including Claude.
“Investment teams shouldn’t have to choose between sophisticated institutional analytics and intuitive AI workflows,” added Falk-Wallace. “Our goal is to bring the two together so investors can move from question to understanding much faster, while keeping the portfolio context that makes the answer useful.”
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