Daloopa
AI-powered financial data infrastructure that automates fundamental data extraction from SEC filings for equity analysts and financial institutions.
Overview
Daloopa is an AI-powered financial data infrastructure company founded in 2019 by former Point72 analyst Thomas Li along with Jeremy Huang (ex-Airbnb/Meta) and Daniel Chen (ex-Microsoft). The New York-based company has raised over $50 million across multiple rounds, including an $18 million Series B led by Touring Capital with Morgan Stanley participation in August 2025, and a $13 million strategic investment from Pavilion Capital in late 2025.
The platform serves over 150 major financial institutions including hedge funds, private equity firms, and investment banks, processing financial documents for 5,000+ public companies globally with claimed accuracy rates exceeding 99%. Daloopa delivers up to 10x more data points per company than competing providers with full source attribution to regulatory filings.
In December 2025, Daloopa launched its Model Context Protocol (MCP) to standardize AI-to-system communication in finance, with connectors for both Anthropic's Claude and OpenAI's ChatGPT. CEO Thomas Li positioned this as making Daloopa "the data infrastructure for AI and agentic workflows in financial services."
Key Features and Benefits
• Excel Add-in Integration: One-click model updates with hyperlinked source verification directly within existing spreadsheets • Retrofitter: Links existing Excel models with source documents and audits historical data inputs with quality-assured data • Updater: Automatically updates models with latest disclosures while maintaining native formatting and reconciling discrepancies with <1% error rate • Scout: AI-powered model building tool that generates complete financial models from prompts with transparent reasoning • API Platform: 8 API endpoints with JSON/CSV formats, webhook notifications, and keyword search functionality • Model Context Protocol: Standardized client-server architecture for AI integrations with containerized deployment support
Use Cases
Financial Modeling
Analysts save an average of 2 hours per ticker each earnings season with 70% reduction in time for new model builds. The platform enables simultaneous updates across all coverage models rather than prioritizing select companies.
Due Diligence and Research
Private equity and hedge funds access 13 years of historical data including company guidance, KPIs, segment breakdowns, and geographic data for comprehensive comparable company analysis.
Compliance and Audit
Hyperlinked source verification enables compliance teams to trace every data point back to original SEC filings and earnings transcripts for regulatory requirements.
Technical Specifications
| Feature | Specification |
|---|---|
| Coverage | 5,000+ public companies globally |
| Accuracy Rate | >99% with full source attribution |
| Data History | 13 years of historical data |
| Security | AES-256 encryption, TLS 1.3 connections |
| Integration | Excel Add-in, API, MCP connectors |
| AI Partners | Anthropic Claude, OpenAI ChatGPT |
| Deployment | Containerized DevOps pipeline support |
Resources
- Daloopa Homepage
- Daloopa Products
- Daloopa API
- Model Context Protocol Guide
- TechCrunch: Daloopa trains AI to automate financial analysts' workflows
Contact Information
Headquarters: New York City, NY Website: https://daloopa.com/ Founded: 2019 Employees: ~300
