Sieve

What is Sieve?

Sieve is a comprehensive data quality platform designed for trading and investment teams that automates the extraction and cleaning of data from financial filings, PDFs, webpages, and other sources. The platform employs a hybrid approach combining advanced machine learning models with expert human reviewers to ensure data accuracy and reliability. Sieve offers both API access and Excel integration, allowing users to seamlessly incorporate clean, analysis-ready data into their existing workflows without manual data entry or extensive quality checks.

Key Features

• Human-in-the-Loop Validation

  Expert human reviewers validate all extracted data through consensus validation, ensuring accuracy and eliminating errors that purely automated systems might miss.

• Multi-Source Data Extraction

  Extracts structured data from diverse sources including SEC filings, financial reports, PDFs, webpages, and even images with consistent formatting.

• Excel Integration

  Native Excel plugin allows users to extract clean data directly into spreadsheets using simple formulas like =SIEVE.GET_DATA(...) without leaving their workflow.

• API-First Architecture

  Robust API enables seamless integration with existing data pipelines and ETL processes for automated, scalable data operations.

• Enterprise Security

  Built for institutional clients with enterprise-grade security measures and compliance standards suitable for financial services organizations.

Use Cases

• Financial Data Processing : Investment firms and hedge funds use Sieve to extract reliable data from SEC filings, earnings reports, and financial statements for quantitative analysis.
• ESG Data Collection : ESG investors leverage the platform to systematically collect and verify environmental, social, and governance data from corporate filings and reports.
• Sell-Side Research Analysis : Financial analysts extract structured data from sell-side research reports to build comprehensive databases for investment decision-making.
• Commodities Trading Intelligence : Commodities-focused investors use Sieve to process market reports and regulatory filings for trading insights and risk management.
• Data Quality Assurance : Organizations replace manual data validation processes with automated extraction and human-verified quality checks to eliminate production errors.

FAQs