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Daloopa
Source-linked financial data infrastructure for AI and agentic investment workflows
Last verified August 15, 2026 · Updated daily
What Daloopa is building
Daloopa is the plumbing that makes AI actually useful in finance. The problem it solves is specific and consequential: when an AI agent produces a financial analysis, the answer is only as reliable as the data it retrieved. Most AI-accessible financial data is web-scraped, inconsistently labelled, and not traceable to an original filing. When the data is wrong, the analysis is wrong, and in investment decisions, that costs money. Daloopa's platform covers 5,500+ public companies globally. Every data point is extracted directly from the original source document (SEC filing, investor presentation, earnings release) and hyperlinked back to it. Fiscal calendars are normalised. Metric definitions are standardised across companies. Historical data goes back up to 14 years. The platform delivers 10 times more data points per company than competing providers. In a benchmark study, AI agent accuracy improved by up to 71 percentage points when grounded in Daloopa's auditable dataset versus web-based retrieval. Delivery is format-agnostic: Excel add-in for traditional analysts, API for programmatic access, cloud-native delivery via Snowflake, Databricks, and AWS S3 for enterprise data teams, and MCP connectors that plug directly into Claude, ChatGPT, Perplexity, and Rogo for agentic workflows. The Partner API launched recently allows third-party developers to build on the data layer directly. The product is not theoretical. 160+ financial institutions are paying customers, Anthropic and OpenAI use it, and the company has doubled revenue year-on-year. Fast Company ranked Daloopa #10 in the Emerging Enterprise category in its 2026 Most Innovative Companies list.
Why this matters
Investment research is one of the largest and most data-intensive white-collar workflows in the world. For decades, it has run on a manual process: analysts pulling numbers from filings, cleaning and reconciling them, building and updating Excel models, before getting to any actual analysis. AI has been able to do the analysis part for two years. The bottleneck is the data input: if the figures going in are wrong, the analysis coming out is wrong. The AI in financial services adoption curve makes this urgent. The Cambridge Centre for Alternative Finance's 2026 Global AI in Financial Services Report found 81% of surveyed firms are now adopting AI, with 40% at advanced adoption levels. Advanced adoption means production workflows, not pilots. Production workflows require data that is accurate, auditable, and traceable. That is Daloopa's entire product proposition. Brighton Park's special advisor for this round was Phil Hadley, former CEO and Chairman of FactSet, one of the largest financial data companies in the world (valued at approximately $17 billion). FactSet and Bloomberg Terminal together have dominated financial data infrastructure for decades. Hadley's involvement signals that Brighton Park understands financial data at the incumbent level and believes Daloopa is building something that matters in the next era. When the former CEO of your most relevant incumbent competitor advises the lead investor, the due diligence is unusually rigorous and the conviction is correspondingly high. Squarepoint Capital's participation is the user validation signal. Squarepoint is a quantitative hedge fund that manages billions in capital through algorithmic strategies. They do not make venture bets for financial returns at their scale. They invested because Daloopa's data is already in their research infrastructure and they want to ensure it remains well-resourced and competitive.
Open roles at Daloopa
5 positions we're tracking. Roles are re-checked daily and removed when filled.
Product Manager
First seen 2 months ago
Product Operations & Analytics Lead
First seen 2 months ago
Customer Success Manager
First seen 2 months ago
Account Executive
First seen 2 months ago
Business Development Representative
First seen 2 months ago
Hiring outlook
Very High. The press release explicitly names team expansion across engineering, product, and go-to-market as a capital use. Revenue doubled year-on-year. Five confirmed live roles on Built In and LinkedIn at the time of writing.
Working at Daloopa
Since 2019, Daloopa has built Source-linked financial data infrastructure for AI and agentic investment workflows. The team is now 50-200 people. Working at a AI company at this stage means defined function but no bureaucracy, you'll own a surface area rather than a ticket queue.
Most openings are based out of New York.
Frequently asked questions
How many jobs does Daloopa have open?
As of June 2026, Daloopa has 5 open positions.
Does Daloopa hire remotely?
Daloopa doesn't have remote openings at the moment. All roles are in New York.
What roles is Daloopa hiring for?
Daloopa is hiring across Product, Operations, Customer, Sales. The most recent opening is Product Manager.
How do I apply for a job at Daloopa?
Use the apply links above, or check our guide to getting hired at Daloopa.
Where is Daloopa based?
Daloopa is headquartered in New York, US.
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