Daloopa is an AI-powered platform designed to automate financial data extraction and modeling, enabling finance professionals to build accurate and dynamic financial models faster. Targeted at equity research analysts, investment professionals, and corporate finance teams, Daloopa significantly reduces the manual workload associated with collecting, inputting, and updating data from financial reports, earnings calls, and regulatory filings.
At its core, Daloopa provides deep data automation through machine learning and natural language processing. It extracts line-item level data from documents such as 10-Ks, 10-Qs, investor presentations, and earnings call transcripts, and feeds that data directly into customizable Excel models. This creates a streamlined workflow where finance professionals can focus on strategic analysis rather than manual data entry.
Features of Daloopa
Automated Data Extraction
Daloopa uses AI to extract granular financial data from company filings, earnings transcripts, and PDFs. This includes metrics like revenue, EBITDA, cash flows, KPIs, and footnotes.
Excel Model Integration
Daloopa syncs extracted data directly into your custom Excel templates, ensuring seamless integration with existing workflows and formulas.
Historical and Real-Time Updates
Models can be kept continuously up to date as new filings are released. Daloopa automatically pushes the latest figures into your spreadsheet without breaking structure or formatting.
Multi-Source Data Coverage
The platform pulls data from a wide range of trusted financial sources including SEC filings, earnings releases, company presentations, and more.
Custom Model Support
Users can work with Daloopa to create tailored templates specific to their industry, company coverage, or modeling needs.
Accuracy and Auditability
Every data point is tagged with a source link, allowing analysts to trace each figure back to the original filing. This enhances transparency and ensures auditability.
Collaboration Tools
Daloopa supports team collaboration, enabling financial teams to work from shared models and data sets with consistency and efficiency.
How Daloopa Works
Daloopa starts with ingestion of public company documents, including SEC filings, investor presentations, and transcripts. The AI system parses these documents using natural language processing and optical character recognition (OCR) to extract relevant financial data points.
These data points are matched to user-defined model structures. Daloopa’s technology identifies which values correspond to which lines in the model and automatically inputs the numbers into an Excel spreadsheet. The tool ensures consistency across historical periods, updates models with new releases, and maintains the integrity of formulas and formatting.
Users are also able to interact with a cloud-based dashboard, where they can search across companies, view historical data trends, and download updated models on demand. For any figure, users can click to see its source within the original document, enabling full traceability.
The platform continuously learns and improves based on user feedback and evolving document formats, ensuring long-term reliability.
Use Cases of Daloopa
Equity Research
Sell-side analysts can automate model maintenance across hundreds of covered companies, reducing the time needed for earnings season updates and freeing up time for client insights.
Investment Management
Buy-side teams use Daloopa to create and maintain accurate, up-to-date models that support investment theses and valuation analysis across sectors.
Private Equity and Venture Capital
Investors can track financial data of public comparables or portfolio companies for benchmarking, diligence, and reporting.
Corporate Finance and FP&A
In-house finance teams use Daloopa to streamline budgeting, forecasting, and competitive benchmarking by integrating real-world financials into planning models.
Consulting and Advisory Firms
Advisors use Daloopa to quickly access and analyze financial data for client presentations, M&A support, or strategic analysis without manually combing through reports.
Pricing of Daloopa
Daloopa does not publish its pricing structure publicly on the website. The platform appears to follow a custom enterprise pricing model based on:
Number of users or seats
Number of companies tracked or covered
Level of customization for Excel templates
Data source integrations
Support and onboarding requirements
Potential clients are encouraged to request a demo and speak directly with the Daloopa sales team to receive a tailored quote based on their organizational needs.
Strengths of Daloopa
Time Efficiency
Automates repetitive and time-consuming financial data collection, significantly reducing hours spent on model maintenance.
Accuracy and Traceability
Each data point is linked to its original source, enhancing audit confidence and ensuring transparency for regulatory and internal review.
Customizable Integration
Fits directly into existing Excel-based workflows without requiring teams to adopt new modeling platforms or rebuild templates.
Scalability
Supports teams with coverage across hundreds of companies and multiple industries, allowing for centralized model management.
Improved Collaboration
Teams can standardize processes and eliminate version control issues with shared templates and synchronized data updates.
Drawbacks of Daloopa
Enterprise Focus
Daloopa is designed for large-scale, professional use. Smaller firms or individual analysts may find the platform too robust or costly for their needs.
No Public Pricing
The lack of transparent pricing can delay decision-making for potential customers who prefer upfront budgeting.
Requires Initial Setup
Although the platform offers customization, initial onboarding and template configuration may require some investment of time and coordination.
Limited to Financial Documents
While excellent at parsing structured financial reports, Daloopa may not be suited for general document analysis beyond its financial niche.
Comparison with Other Tools
Compared to legacy solutions like FactSet, CapIQ, or Thomson Reuters, Daloopa offers a more automated and AI-driven experience specifically for financial modeling. While traditional platforms provide robust databases, they often lack direct integration into user-defined Excel models with real-time updating.
Against newer tools like AlphaSense or Sentieo, which offer document search and summarization features, Daloopa stands out for its deep integration with Excel modeling workflows. AlphaSense helps with idea generation and sentiment analysis, whereas Daloopa focuses purely on automating the number-crunching backbone of financial analysis.
Daloopa is especially beneficial for organizations that rely heavily on customized models and require pinpoint accuracy, historical consistency, and real-time updates.
Customer Reviews and Testimonials
Publicly available testimonials highlight several key benefits from users:
Users report saving dozens of hours during earnings season by automating model updates.
Financial analysts appreciate the ability to maintain hundreds of models with minimal manual effort.
Teams mention improved accuracy, better audit trails, and faster turnaround time for reports.
Clients also value Daloopa’s responsive customer support and willingness to build custom features as needed.
While detailed reviews are not prominently featured on third-party review sites, Daloopa’s client base appears to include large investment banks, asset managers, and financial research firms, reinforcing its enterprise credibility.
Conclusion
Daloopa represents a major leap forward in the automation of financial data extraction and modeling. By leveraging artificial intelligence, the platform empowers financial professionals to build and maintain complex models with unmatched speed, accuracy, and transparency. For teams managing high volumes of company coverage or requiring rapid turnaround on financial analysis, Daloopa provides a scalable and customizable solution that integrates seamlessly into existing workflows.
While it may not be designed for smaller users or non-financial use cases, its value proposition is clear for equity research teams, investment firms, and corporate finance departments looking to modernize their approach to data modeling. With continued innovation and enterprise-grade support, Daloopa is helping redefine what’s possible in financial operations.
