Third Bridge Taps Anthropic’s Claude For Financial Services for Expert Insights
Third Bridge, a leading global expert network and investment research provider, has announced a major integration with Anthropic’s Claude for Financial Services, in collaboration with Aiera. The partnership embeds Third Bridge’s vast library of proprietary expert interview transcripts directly into Claude’s AI environment — allowing analysts, investors, and financial institutions to query expert insights in real time.
Using Aiera’s Model Context Protocol (MCP) server, the integration securely connects Third Bridge’s qualitative data with Claude’s agentic AI research capabilities. This enables financial professionals to combine expert perspectives with quantitative data, internal models, and market analytics — producing quicker, richer, and more contextualized insights.
Takeaway
Revolutionizing Financial Research Workflows
Traditionally, accessing and synthesizing expert interviews has been a manual, time-intensive process. The Claude integration changes that — turning Third Bridge’s proprietary data into a dynamic, queryable layer inside a secure AI research environment. Analysts can now ask open-ended questions and receive synthesized answers that combine expert testimony with market data, saving time and reducing information silos.
Mike Grubert, Managing Director at Third Bridge, emphasized that the collaboration represents a major evolution in financial research. “By integrating directly with Claude for Financial Services, we are fundamentally leveraging AI to improve the financial research ecosystem,” he said. “Analysts can now ask complex questions and have Claude synthesize expert perspectives alongside other data points — accelerating due diligence from weeks to days.”
Takeaway
How It Works: Secure, Scalable Data Access
Through Aiera’s MCP integration, Claude can securely access Third Bridge’s interview library while maintaining full audit trails and data governance standards required in enterprise environments. The Model Context Protocol allows AI models like Claude to draw context dynamically from proprietary datasets without compromising security or compliance — a key innovation for institutional-grade AI adoption.
This setup enables Claude to use verified expert insights as a “first-class data source,” alongside structured financial databases and internal research tools. For end users, this means they can run comprehensive analysis, scenario modeling, or sentiment tracking — all with embedded human expertise as part of the data foundation.
Takeaway
Industry Impact: Human Expertise Meets Machine Scale
Third Bridge CEO Emmanuel Tahar described the collaboration as a bridge between human expertise and machine-driven analytics. “By natively incorporating Third Bridge’s deep qualitative insights directly into Claude’s agentic framework, we are bridging the gap between human expertise and machine scale,” he said. “This provides clients with a unified intelligence layer that delivers auditable, comprehensive context and establishes a new standard for speed and confidence in investment decision-making.”
Anthropic’s Claude for Financial Services is purpose-built for demanding institutional use cases such as research, due diligence, and financial modeling. It features specialized financial reasoning capabilities, auditable output trails, and compliance-grade security, enabling clients to integrate AI directly into sensitive research workflows.
Takeaway
Anthropic’s Expanding Financial Services Ecosystem
Nicholas Lin, Head of Product for Financial Services at Anthropic, said that high-quality, verified data providers like Third Bridge are central to Claude’s financial ecosystem. “Combining Claude’s intelligence with LSEG and Third Bridge data provides real value,” Lin noted. “With trusted data, Claude can summarize earnings calls, analyze diligence materials, trigger workflows, and surface market signals with enterprise-grade accuracy.”
This integration follows Anthropic’s broader expansion in financial services, including recent partnerships with the London Stock platform Group (LSEG) and other data infrastructure providers. Together, these collaborations are building an open, interoperable framework for AI in institutional finance.
