Dividend Data vs Dokta

Comprehensive Spreadsheet Integration

The platform provides seamless integration with both Google Sheets and Microsoft Excel via dedicated add-ins. Users access data through 16+ custom functions, such as DIVIDENDDATA_DIVIDENDS, DIVIDENDDATA_RATIOS, and DIVIDENDDATA_QUOTE. These functions allow for dynamic, live data retrieval directly into spreadsheet cells, transforming static sheets into powerful, auto-updating analysis tools. The integration requires no coding, maintaining the familiar spreadsheet environment while supercharging its capabilities with professional data feeds.

Extensive Historical & Fundamental Data Library

Dividend Data grants instant access to a deep historical database covering 30+ years of market data. This includes not only dividend history and forward-looking metrics but also complete fundamental data: income statements, balance sheets, cash flow statements, and over 100 key financial ratios (e.g., P/E Ratio, Debt-to-Equity). The coverage of 80,000+ tickers ensures data is available for a vast array of global stocks, ETFs, and other securities, supporting thorough historical trend analysis and comparative fundamental research.

Dividend-First Analytical Functions

Tailored specifically for income investors, the tool offers specialized functions that output critical dividend metrics. Users can retrieve forward annual dividends, forward dividend yields, next ex-dividend dates, payout ratios, and dividend growth rates with single formulas. This focused feature set allows for rapid screening, yield calculation, and sustainability analysis directly within a portfolio model or research sheet, streamlining the workflow for constructing and monitoring dividend growth portfolios.

Free Tier with Generous Monthly Credits

A key differentiator is the sustainable free access model. The platform offers a permanent free tier that provides 2,500 credits per month without trial expiration or credit card requirements. This allows users to perform substantial monthly analysis, such as pulling data for hundreds of stock queries, at zero cost. This model lowers the barrier to entry for individual investors and provides real utility before any upgrade consideration.

AI-Powered Document Analysis

Dokta's core functionality is its advanced AI and OCR processing engine. Upon document upload (photo, scan, or PDF), the system automatically reads, classifies, and extracts key structured data such as document type, total amount, due date, and involved parties in less than 60 seconds. This eliminates manual data entry, ensures accuracy, and instantly converts static documents into actionable items within the platform's workflow, forming a searchable digital archive.

Automated Invoicing & Quote Management

The platform provides comprehensive tools for the billing cycle. Users can create professional invoices and quotes in a few clicks. A standout feature is the ability to send quotes with an online acceptance link, enabling clients to approve digitally, after which conversion to a final invoice is a one-click operation. For freelancers on daily rate (TJM) contracts, Dokta supports automated monthly invoice generation based on the contract terms, streamlining recurring billing.

Real-Time Cash Flow & Anomaly Detection

Dokta offers a centralized financial dashboard that displays key metrics in real time: invoiced revenue, collected revenue, unpaid invoices, and VAT liabilities. This is complemented by a 12-month graphical trend analysis. Proactively, the AI engine includes an anomaly detection system that identifies potential issues such as modified IBAN details, duplicate invoices, inconsistent VAT rates, or missing sequential numbering, providing an essential layer of financial oversight.

Integrated Client & Supplier Database

The platform automatically constructs and enriches a relational database of clients and suppliers by extracting entity details from every processed document. It can perform automatic SIRET number lookup (for French entities) to enrich profiles and includes a payment scoring system based on historical data. This creates a complete, intelligent history per contact, facilitating better relationship management and providing context for all financial interactions.

Automated Dividend Portfolio Tracking

Investors can build a dynamic dividend portfolio tracker in their preferred spreadsheet. By using formulas like DIVIDENDDATA_DIVIDENDS to pull yield and payment data for each holding, the portfolio sheet can automatically calculate projected annual income, portfolio yield, and track ex-dividend dates. This eliminates manual data entry and ensures the portfolio dashboard always reflects the latest declared dividends and share prices.

Fundamental Stock Screening and Analysis

Analysts and investors can create custom stock screens using the live data functions. By building a sheet with columns for various metrics (e.g., P/E ratio, dividend yield, payout ratio, EPS growth), users can paste a list of tickers and instantly populate a comparable analysis matrix. This facilitates rapid identification of stocks meeting specific fundamental criteria, such as those with a yield above 3%, a P/E below 20, and a payout ratio under 60%.

Historical Financial Performance Research

For deep-dive research on a specific company, users can construct multi-year financial models. Formulas can pull 10+ years of annual revenue, net income, EPS, and dividend per share data into adjacent columns, enabling the creation of charts and the calculation of compound annual growth rates (CAGR) for critical financial metrics. This supports thorough due diligence on a company's long-term financial health and dividend growth trajectory.

Educational Modeling and Backtesting

Students and investing enthusiasts can use the historical price and dividend data to build educational models. For instance, they can create a sheet to backtest a dividend reinvestment plan (DRIP) strategy by pulling historical prices and dividend dates to simulate growth over time. This hands-on access to real historical data provides a practical tool for learning about equity analysis and portfolio mechanics.

Freelance IT Developer / Consultant

For IT freelancers operating on Time and Materials (TJM) contracts, Dokta automates the entire invoicing pipeline. The system can be configured to generate monthly invoices automatically based on the contracted rate, sending them for one-click validation. This allows the freelancer to focus on development work while Dokta handles payment tracking, sends automated reminders for late payments, and maintains a clear record of all client transactions and project-related documents.

Creative Freelancer / Project-Based Worker

Graphic designers, photographers, and other project-based creatives benefit from Dokta's streamlined proposal-to-payment workflow. They can create a quote and send it via a professional online acceptance link to the client. Upon client approval, the quote is converted to an invoice with a single click. Dokta then manages the payment follow-up, chases late invoices with professional reminders, and keeps all project documents and client communications organized in one place.

Auto-Entrepreneur / Micro-Entrepreneur

This user group requires simplicity and compliance. Dokta generates legally compliant invoices, automatically tracks revenue against the micro-entrepreneur income ceiling, and provides alerts for upcoming URSSAF social charge payment deadlines. The real-time cash flow dashboard gives a clear, immediate view of business health without complex accounting knowledge, and the CSV export feature simplifies year-end accounting procedures.

Growing Small Business (SMB)

Small businesses managing multiple clients, suppliers, and contracts use Dokta as a centralized document command center. The AI processes incoming bills and outgoing invoices, automatically populating the cash flow forecast. Anomaly detection safeguards against fraud or errors, and the automated task generation from documents (e.g., "pay this invoice by X date") ensures no deadline is missed, improving operational reliability and financial control.

Dividend Data is a specialized financial data platform engineered to provide institutional-grade stock market intelligence directly within the workflow of fundamental and dividend investors. Its core product is a powerful spreadsheet add-in for Google Sheets and Microsoft Excel that eliminates the traditional barriers to accessing deep financial data. The platform delivers over 30 years of historical and real-time data for more than 80,000 global tickers through a suite of simple, custom spreadsheet formulas. Users can instantly pull critical metrics such as dividend amounts, yields, payout ratios, growth rates, complete financial statements, earnings data, valuation ratios, and price history without requiring API keys, coding knowledge, or manual copy-pasting from external sources. Built by a dividend investor for the community, Dividend Data distinguishes itself with a permanently free tier offering 2,500 monthly credits, robust functionality across both major spreadsheet ecosystems, and a focus on the specific data points that income-focused and value investors need to make informed decisions. It is designed for individual investors, financial analysts, and portfolio managers who demand comprehensive, reliable data but seek to avoid the complexity and high cost typically associated with professional financial data terminals.

Dokta is a sophisticated AI-powered document management and business automation platform engineered specifically for freelancers, solo entrepreneurs, auto-entrepreneurs, and small to medium-sized businesses (SMBs). The platform is designed to eliminate administrative inefficiencies by placing AI at the core of document processing. Users can upload any document, such as invoices, quotes, or contracts, and Dokta's AI engine, powered by Claude (Anthropic), performs Optical Character Recognition (OCR), classifies the document type, and extracts critical data fields including amounts, due dates, and client details in under 60 seconds. It manages the entire document lifecycle, from creation to payment tracking. This includes generating professional invoices and quotes, automating payment reminders, managing contract deadlines, and creating actionable tasks directly from document content. The system autonomously builds a searchable client and supplier database, provides real-time cash flow analytics with 12-month graphical trends, and facilitates accounting through CSV export. Hosted on AWS in Paris with AES-256 encryption, Dokta guarantees 100% GDPR compliance, ensuring data sovereignty and security for European users. Its core value proposition is transforming document management from a manual, error-prone task into an automated, intelligent, and centralized operational hub.

What data can I access with the free tier?

The free tier provides full access to all of Dividend Data's 16+ custom functions and the entire database of over 80,000 tickers and 30+ years of history. Your usage is limited by a monthly credit allowance of 2,500 credits. Each data point retrieved (e.g., one cell with a price, a dividend yield, an EPS figure) typically consumes one credit. This allows for hundreds to thousands of data points per month, suitable for substantial personal analysis and portfolio tracking.

How does the spreadsheet add-in get installed?

For Google Sheets, you install the "Dividend Data" add-on directly from the Google Workspace Marketplace. For Microsoft Excel, you install the "Dividend Data" add-in from the Microsoft AppSource store within Excel. Both processes are straightforward, following the standard installation flow for each platform. Once installed, the custom functions become available in your spreadsheet, and you can start using them immediately after a quick account sign-up.

Is the data provided live and real-time?

The data is live and reflects the most recent information available from Dividend Data's providers. For market quotes like stock price, it is typically real-time or delayed based on the data feed. Fundamental data, such as financial statements and dividends, is updated as soon as the information is publicly released and processed. The average response time for a data request is 0.84 seconds, ensuring your spreadsheets update quickly.

Do I need to know how to code or use APIs?

No coding or API knowledge is required. Dividend Data is designed specifically to be a no-code solution. All data integration is handled through simple, pre-built spreadsheet formulas that work identically to native functions like SUM() or VLOOKUP(). You only need to know the ticker symbol and the metric code (provided in the documentation) to retrieve any data point.

How does Dokta ensure the security and privacy of my documents?

Dokta is built with a strong security-first architecture. All data is hosted on Amazon Web Services (AWS) in Paris, France, ensuring physical and legal data sovereignty within the European Union. Documents and data are encrypted at rest using AES-256 encryption. The platform is fully compliant with the General Data Protection Regulation (GDPR), governing how personal data is processed and stored. No manual access to your documents is performed without explicit consent.

What types of documents can Dokta process?

Dokta's AI engine is optimized to process a wide range of business documents essential for freelancers and SMBs. This includes incoming and outgoing invoices, quotes, proposals, and various types of contracts. The system accepts documents in multiple formats: PDF files, scanned images, and even photographs taken with a smartphone. The AI performs classification to identify the document type before proceeding with precise data extraction.

What happens if the AI makes an error in data extraction?

Dokta is designed for high accuracy but operates on a human-in-the-loop principle for validation. After the AI completes its sub-60-second analysis, the extracted data is presented to the user in an interface for review and confirmation. The user retains full control to correct any field before the data is finalized and integrated into the system. This ensures accuracy while still saving the vast majority of manual entry time.

Can I use Dokta for accounting and tax reporting?

While Dokta is not a certified accounting software, it provides robust features to support accounting and tax preparation. It automatically tracks all invoiced and paid amounts, calculates VAT totals, and allows you to categorize expenses. The key feature is the ability to export all financial data, including client lists, transaction histories, and VAT summaries, into a standardized CSV file format that can be directly imported into most accounting software or provided to your accountant.

Dividend Data is a specialized financial data add-on for Google Sheets and Microsoft Excel, falling into the category of fundamental and dividend investment analysis tools. It provides direct spreadsheet integration for historical dividend data, financial statements, and key metrics without requiring programming skills or API management. Users may explore alternatives for various reasons, including specific budget constraints, the need for different data points like options or macroeconomic indicators, integration with other platforms such as trading software, or a preference for a standalone desktop application rather than a spreadsheet add-on. The core requirement often remains consistent: reliable, historical financial data to inform investment decisions. When evaluating an alternative, key considerations should include the depth and historical range of the dividend dataset, the total cost relative to your data consumption, the ease of integration with your existing workflow, and the breadth of supplementary fundamental metrics offered, such as financial ratios and earnings data.

Dokta is an AI-powered document management platform operating within the business and finance software category. It automates the lifecycle of key business documents like invoices, quotes, and contracts for freelancers, solo entrepreneurs, and SMBs, centralizing data extraction, creation, and tracking. Users may seek alternatives to Dokta for various reasons, including specific budget constraints, the need for more advanced or different feature sets, integration requirements with other business tools, or a preference for platforms hosted in different geographic regions. The search often hinges on finding the optimal balance between automation depth and cost. When evaluating alternatives, key criteria include the platform's core document processing capabilities, such as AI-driven data extraction accuracy and speed. Other critical factors are the breadth of the document lifecycle management features, pricing structure and scalability, data security and compliance certifications, and the availability of essential integrations with accounting, CRM, or payment systems.