Daloopa, a financial data infrastructure provider powering AI and agentic workflows for investment firms, has secured $47m in a Series C funding round.
Brighton Park Capital led the raise, with Squarepoint Capital, Touring Capital, and Nexus Venture Partners all participating. The capital will be deployed to accelerate growth of Daloopa’s platform and to scale the company’s engineering, product, and go-to-market teams.
The funding arrives as investment firms transition AI from experimental use cases into live production workflows, where the standard of data accuracy becomes far more consequential. Daloopa argues that the true constraint in AI-driven finance is not the intelligence of the underlying models but the quality of the data feeding them. Issues such as misaligned fiscal calendars or inconsistent metric definitions, even when minor, can materially distort outputs across high-stakes applications including valuation, earnings analysis, and portfolio modelling.
The company’s platform currently spans more than 5,500 public companies worldwide, offers up to ten times the number of data points per company compared to rival providers, and links every data point back to its original filing for full auditability. Investment firms rely on the platform across a broad range of tasks, from quarterly analysis and scenario modelling through to AI-assisted research and reporting.
Daloopa has also made a series of product and partnership advances that have strengthened its position at the centre of the emerging AI investment research stack. The company recently expanded access to its data through Model Context Protocol connectors with OpenAI’s ChatGPT, Anthropic’s Claude, Perplexity, and Rogo, embedding structured financial data directly into tools analysts already use day-to-day.
It also published a benchmark study demonstrating that AI agent accuracy in financial retrieval improved by up to 71 percentage points when grounded in structured, auditable data rather than web-based sources. On the platform side, Daloopa has added programmatic access via API as well as cloud-native delivery through Snowflake, Databricks, and AWS S3. The company is also launching a Partner API to enable third-party developers and select partners to build AI-driven workflows and product integrations using its financial data.
Daloopa was built to address a structural problem that predates AI: analysts were historically forced to spend hours manually extracting and validating data from company filings. AI tools have inherited the same underlying challenge, as most draw on web-sourced inputs that lack standardisation or source attribution, making their outputs unreliable for professional investment use. Daloopa’s approach centres on providing structured, source-linked financial data that can serve as a trusted foundation for both human analysts and automated systems.
Daloopa CEO Thomas Li said, “We’re seeing firms move from early experimentation toward deploying AI in real investment workflows, and that changes the requirements entirely. It’s no longer enough for models to simply generate answers; they must be accurate and fully traceable. Our focus is on building the data infrastructure that makes that possible, so firms can trust what AI is producing.”
Copyright © 2026 FinTech Global
