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Daloopa

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Daloopa is a free-trial AI financial modeling tool that extracts auditable data from SEC filings into Excel, covering over 3,500 public companies with 99% accuracy.

Pricing Model
free_trial
Skill Level
All Levels
Best For
Investment ManagementPrivate EquityEquity ResearchCorporate Finance
Use Cases
Financial ModelingData ExtractionExcel AutomationEarnings Analysis
Visit Site
4.5/5
Overall Score
4+
Features
1
Pricing Plans
0
User Reviews
Updated 21 May 2026
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What is Daloopa?

Daloopa is an AI-powered financial data platform that extracts structured, auditable data from SEC filings, investor presentations, earnings transcripts, and press releases, and delivers it directly into Excel financial models via a native add-in or data feed. Every extracted data point is hyperlinked to its original source document, so analysts can trace any figure back to the 10-K, 10-Q, or earnings release it came from — a compliance and quality assurance requirement that manual data entry cannot match at scale. Equity research analysts and buy-side portfolio managers face a recurring bottleneck during earnings season: updating financial models with newly reported figures from dozens of companies simultaneously is a labor-intensive, error-prone process that can occupy an analyst for an entire trading day. Daloopa's one-click Updater feature reconciles discrepancies, highlights newly disclosed metrics, and refreshes models immediately following earnings releases — a workflow that converts a multi-hour task into a minutes-long operation. As of April 2026, Daloopa expanded its AI partnership ecosystem with a new Perplexity integration, allowing investment teams to query their Daloopa data license directly within Perplexity's interface through a bring-your-own-license model — building on existing connectors with ChatGPT and Claude. Daloopa is not the right tool for individual retail investors or small teams seeking low-cost fundamental data access. The platform targets institutional finance workflows — hedge funds, mutual funds, private equity firms, and investment banks — and pricing follows a custom enterprise model available on request rather than self-serve tiers. Teams seeking broad market data at a lower price point will find FactSet or Bloomberg Terminal more appropriate, albeit at significantly higher cost for full feature parity.

Daloopa is a free-trial AI financial modeling tool that extracts auditable data from SEC filings into Excel, covering over 3,500 public companies with 99% accuracy.

Daloopa is widely used by professionals, developers, marketers, and creators to enhance their daily work and improve efficiency.

Key Features

1
Auditable Data
Every data point extracted from SEC filings, investor presentations, and earnings transcripts is hyperlinked directly to the source document. Analysts can click any figure in their Excel model and jump immediately to the exact page and line in the original filing — a requirement for institutional compliance and model audit workflows.
2
1-Click Updates
The Updater feature reconciles existing Excel models with newly reported earnings data immediately following a release, highlights metrics that are disclosed for the first time, and flags discrepancies between prior and restated figures — eliminating the manual comparison step that consumes analyst time during earnings season.
3
Custom Dashboards
Users can configure tailored Excel data sheets and dashboard layouts that match their existing modeling conventions, pulling structured financial data into pre-built model templates without reformatting. The Excel add-in integrates directly into existing workbooks without requiring a separate application.
4
Extensive Data Coverage
Covers 3,500+ public companies with 10+ years of historical financial data including KPIs, adjustments, and non-standard metrics specific to each sector. Data is sourced from 10-Ks, 10-Qs, investor presentations, and earnings call transcripts, and updated rapidly following each earnings release.

Pros & Cons

✓ Pros (4)
Time Efficiency Reduces financial model update time during earnings season from several hours of manual SEC filing review and data entry to a one-click operation — a measurable productivity gain for equity research teams covering 20+ companies across a single reporting period.
High Data Accuracy The platform reports an average extraction accuracy rate exceeding 99%, achieved through a combination of proprietary AI parsing and human quality assurance review on every extracted data point — a higher verification standard than pure AI extraction pipelines.
User-Friendly Interface The Excel add-in integrates directly into existing analyst workflows without requiring migration to a separate application or adoption of a new modeling environment, reducing the change management overhead that slows enterprise software adoption in financial teams.
Scalability Designed to support institutional-scale data requirements — hedge funds managing large equity portfolios, investment banks running simultaneous deal analysis, and research teams covering broad sector universes — without the manual data maintenance overhead that limits scalability in traditional modeling workflows.
✕ Cons (3)
Learning Curve Analysts new to Daloopa's Excel add-in and data sheet architecture typically require onboarding sessions before they can configure models to match their existing templates — the tool's depth means setup time is non-trivial for teams with complex, custom-built financial models.
Dependency on Internet Model updates, data feeds, and the one-click Updater all require an active internet connection. While downloaded data sheets can be reviewed offline, live data refresh and new earnings extraction are not available in disconnected environments — a constraint for analysts working in air-gapped or restricted network environments.
Premium Cost Custom enterprise pricing — available on request rather than via self-serve tiers — reflects a platform built for institutional finance teams with dedicated technology budgets. Smaller firms, boutique advisory shops, or individual analysts will likely find the licensing cost prohibitive relative to lower-coverage alternatives.

Who Uses Daloopa?

Hedge Funds
Using Daloopa's one-click Updater to refresh financial models across large equity portfolios during earnings season, replacing the analyst hours previously spent manually transcribing reported figures from SEC filings into existing Excel models.
Equity Research Analysts
Connecting Daloopa's Excel add-in to sector coverage models to maintain 10+ years of auditable historical data per company, enabling rapid relative valuation work without spending analyst cycles on data collection and formatting.
Investment Bankers
Accessing Daloopa's structured financial data feed to build and update comparable company analysis templates under tight deal timelines, with hyperlinked source verification available for every figure included in client-facing models or presentations.
Private Equity Firms
Using Daloopa's coverage of public comparables to benchmark portfolio company performance against sector peers, pulling structured historical financials into standard reporting templates without assigning analyst time to manual data extraction from public filings.
Uncommon Use Cases
Academic institutions incorporating Daloopa into graduate finance programs to teach financial modeling with real, auditable company data; non-profit organizations with endowment investment functions using the platform for financial benchmarking and grant portfolio analysis.

Daloopa vs Luna vs Shipixen vs WhatDo

Detailed side-by-side comparison of Daloopa with Luna, Shipixen, WhatDo — pricing, features, pros & cons, and expert verdict.

Compare
D
Daloopa
Free
Visit ↗
Luna
Freemium
Visit ↗
Shipixen
Paid
Visit ↗
WhatDo
Free
Visit ↗
💰Pricing
FreeFreemiumPaidFree
Rating
🆓Free Trial
Key Features
  • Auditable Data
  • 1-Click Updates
  • Custom Dashboards
  • Extensive Data Coverage
  • Database Access
  • AI-Powered Messaging
  • Task Management
  • Multichannel Outreach
  • AI Content Generation
  • SEO Optimization
  • Comprehensive Templates
  • One-Click Deployment
  • Comprehensive Destination Coverage
  • AI-Powered Itinerary Planning
  • Real-Time Booking
  • Interactive Travel Guides
👍Pros
Reduces financial model update time during earnings sea
The platform reports an average extraction accuracy rat
The Excel add-in integrates directly into existing anal
Automating lead discovery, AI message drafting, and fol
Luna's pricing replaces the cost of separate data enric
AI-personalized emails referencing contact-specific dat
Generating a complete Next.js codebase with branding, S
Shipixen operates on a one-time purchase model with no
Brand input fields, theme selection, and one-click depl
Consolidating destination research, itinerary generatio
WhatDo's integration with multiple travel services posi
40,000+ destination coverage means WhatDo has useful co
👎Cons
Analysts new to Daloopa's Excel add-in and data sheet a
Model updates, data feeds, and the one-click Updater al
Custom enterprise pricing — available on request rather
Sales reps new to AI-assisted outreach often spend the
While Luna supports LinkedIn and calling, the platform'
The free tier provides access to core features at low v
Developers unfamiliar with Next.js, MDX, or Tailwind CS
Payment processing via Stripe, LemonSqueezy, or Paddle
Shipixen's desktop application runs on macOS and Window
Real-time booking integration, AI itinerary generation,
For travelers visiting a destination with very limited
WhatDo's full feature set — preference calibration, iti
🎯Best For
Hedge FundsSmall and Medium EnterprisesE-commerce BusinessesSolo Travelers
🏆Verdict
Compared to the manual process of copying figures from 10-Qs…
Compared to manual cold outreach workflows, Luna reduces pro…
For startup founders and freelance developers building Next.…
Compared to manually coordinating itinerary planning across …
🔗Try It
Visit Daloopa ↗Visit Luna ↗Visit Shipixen ↗Visit WhatDo ↗
🏆
Our Pick
Daloopa
Compared to the manual process of copying figures from 10-Qs into Excel, Daloopa reduces an earnings-season model update
Try Daloopa Free ↗

Daloopa vs Luna vs Shipixen vs WhatDo — Which is Better in 2026?

Choosing between Daloopa, Luna, Shipixen, WhatDo can be difficult. We compared these tools side-by-side on pricing, features, ease of use, and real user feedback.

Daloopa vs Luna

Daloopa — Daloopa is an AI Tool that automates financial data extraction from SEC filings into Excel, with every data point hyperlinked to its source and a 99% accuracy r

Luna — Luna is an AI Tool that combines a 275 million contact database with AI-generated personalized messaging and multichannel outreach capabilities across email, Li

  • Daloopa: Best for Hedge Funds, Equity Research Analysts, Investment Bankers, Private Equity Firms, Uncommon Use Cases
  • Luna: Best for Small and Medium Enterprises, Startups, Sales Professionals, Marketing Agencies, Uncommon Use Cases

Daloopa vs Shipixen

Daloopa — Daloopa is an AI Tool that automates financial data extraction from SEC filings into Excel, with every data point hyperlinked to its source and a 99% accuracy r

Shipixen — Shipixen is an AI Tool that eliminates the boilerplate tax on Next.js SaaS development — the repetitive scaffold setup that delays every new project regardless

  • Daloopa: Best for Hedge Funds, Equity Research Analysts, Investment Bankers, Private Equity Firms, Uncommon Use Cases
  • Shipixen: Best for E-commerce Businesses, Digital Marketing Agencies, Startup Founders, Freelance Developers, Uncommon

Daloopa vs WhatDo

Daloopa — Daloopa is an AI Tool that automates financial data extraction from SEC filings into Excel, with every data point hyperlinked to its source and a 99% accuracy r

WhatDo — WhatDo is an AI Tool that integrates destination discovery, personalized itinerary planning, and real-time booking across flights, accommodations, and activitie

  • Daloopa: Best for Hedge Funds, Equity Research Analysts, Investment Bankers, Private Equity Firms, Uncommon Use Cases
  • WhatDo: Best for Solo Travelers, Adventure Seekers, Cultural Enthusiasts, Food Lovers, Uncommon Use Cases

Final Verdict

Compared to the manual process of copying figures from 10-Qs into Excel, Daloopa reduces an earnings-season model update from several hours to under five minutes — the primary limitation is that custom enterprise pricing makes it inaccessible for smaller teams or individual analysts who cannot justify the license cost.

FAQs

2 questions
How accurate is Daloopa's financial data extraction?
Daloopa reports an average extraction accuracy rate exceeding 99%, achieved through a combination of proprietary AI parsing technology and human quality assurance review on every data point. Every figure is hyperlinked to its original SEC filing, investor presentation, or earnings transcript, enabling analysts to independently verify any extracted value.
Does Daloopa integrate with Excel?
Yes — Daloopa offers a native Excel add-in that pulls structured financial data directly into existing analyst workbooks. Users can configure data sheets to match their modeling conventions and use the one-click Updater to refresh models immediately following earnings releases without manual data entry or reformatting.

Expert Verdict

Expert Verdict
Compared to the manual process of copying figures from 10-Qs into Excel, Daloopa reduces an earnings-season model update from several hours to under five minutes — the primary limitation is that custom enterprise pricing makes it inaccessible for smaller teams or individual analysts who cannot justify the license cost.

Summary

Daloopa is an AI Tool that automates financial data extraction from SEC filings into Excel, with every data point hyperlinked to its source and a 99% accuracy rate reported by the platform. Coverage spans 3,500+ public companies with 10+ years of historical data.

It is suitable for beginners as well as professionals who want to streamline their workflow and save time using advanced AI capabilities.

User Reviews

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