Thinknum provides a cloud platform that continuously scrapes and normalizes alternative data from public web sources, delivering structured datasets on company activities such as hiring trends, product pricing, store openings, and inventory movements. Users can query the data through a drag‑and‑drop UI or an enterprise‑grade API, visualize results with built‑in widgets, and set threshold‑based alerts, enabling analysts to monitor corporate signals without building their own data pipelines.
Funding
$11.6M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Capital allocators and corporate analysts lack timely, structured data on granular company activities such as hiring trends, product pricing, store openings, and inventory movements, because these signals are scattered across public web sources and require custom scraping and engineering effort to collect and normalize.
Solution
Thinknum delivers a cloud‑based platform that continuously scrapes, cleans, and normalizes alternative data from millions of web pages, turning unstructured web content into ready‑to‑query datasets. Users can build and share SQL‑like queries through an intuitive UI, visualize results with built‑in maps, charts, and word‑cloud widgets, and set threshold‑based alerts that notify them of material changes. The service maintains a historical archive covering over 450,000 public and private companies, enabling back‑testing and trend analysis without any in‑house data‑engineering. An enterprise‑grade API provides programmatic access for integration with existing analytics stacks or BI tools.
Target Audience
Primary users are investment analysts, quantamental teams, and ESG researchers who need high‑frequency corporate activity signals, as well as corporate strategy groups seeking competitive intelligence on hiring, pricing, and expansion trends.
Features
- Automated web‑crawling pipeline with change detection and daily data refresh for job listings, retail product pricing, store locations, property rentals, car inventory, and social‑app usage.
- Unified schema and singular naming convention across all datasets, supporting fast ad‑hoc queries without schema mapping.
- Drag‑and‑drop query builder and full‑text search that returns results in seconds, eliminating the need for engineering resources.
- Pre‑configured visualizations (geospatial heat maps, time‑series charts, word clouds) and customizable dashboard widgets for rapid insight generation.
- Real‑time alert engine that triggers email or webhook notifications when metric thresholds are crossed.
- RESTful API with OAuth2 authentication, pagination, and bulk export options for seamless integration with BI platforms or proprietary models.
- Secure, encrypted data storage with role‑based access controls and audit logging to meet compliance requirements.