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No-code robots that scrape and monitor any website

Automated web extraction and a trillion-fact Knowledge Graph
Diffbot is unusually differentiated: its automatic, vision-based extraction and its Knowledge Graph of a trillion-plus facts are hard for most competitors to match, and it is a favorite among developers who need clean structured data or entity intelligence at scale. The trade-offs are a credit-based pricing model that can get expensive for Knowledge Graph queries, a developer-first experience that is not no-code, and, as with any large-scale crawl-derived dataset, the need to validate coverage and accuracy for your specific entities. It is a strong pick for technical teams, less so for non-technical users.
Diffbot automatically extracts structured data from web pages using computer vision and ML, and maintains a Knowledge Graph of over 10 billion entities and a trillion-plus facts. It is a developer-first platform with extraction APIs, Crawlbot, and Enhance, offering a free credit tier and credit-based paid plans. It is a standout for web-scale structured data and entity intelligence, but is technical and can be costly at scale.
Diffbot's extraction APIs (for articles, products, discussions, and more) automatically parse arbitrary web pages into structured JSON using computer vision and ML, without site-specific rules. Its Crawlbot can crawl entire sites, and Diffbot Enhance can append firmographic and entity data to records. The result is that developers can extract clean structured data from pages they have never configured for. The flagship differentiator is the Diffbot Knowledge Graph, a machine-constructed graph reportedly spanning over 10 billion entities and more than a trillion structured facts, refreshed continuously from crawling the public web. It powers use cases in market intelligence, lead enrichment, news monitoring, and research, queried via API. Diffbot was founded in 2008 (formally around 2012) by Mike Tung and is based in the Bay Area. It raised a relatively modest amount of venture funding, including a 2016 Series A led by Tencent and Felicis, and has operated as a focused, technically deep company. It is developer-oriented and priced with a credit model that can suit both experimentation and heavy production use.
Diffbot automatically extracts structured data from any web page using computer vision and ML, and maintains a Knowledge Graph of over 10 billion entities and a trillion-plus facts. Founded in 2008 by Mike Tung, it raised a modest ~$12.5M including a 2016 Tencent/Felicis Series A. It is a developer-first platform with extraction APIs, Crawlbot, and Enhance, priced on credits with a free tier. Strong for web-scale data and entity intelligence.
Diffbot was founded by Mike Tung (early work from 2008, company established in the early 2010s) and is based in the San Francisco Bay Area. It has stayed a focused, technically deep company centered on automatic web extraction and its Knowledge Graph.
Diffbot raised a relatively modest amount of venture capital, around $12.5M total, including a $10M Series A in 2016 led by Tencent and Felicis Ventures, with Bloomberg Beta among earlier backers. It has operated with a lean, engineering-driven model rather than aggressive fundraising.
Its extraction APIs turn arbitrary pages into structured JSON without site-specific rules, Crawlbot crawls entire sites, and Enhance appends entity and firmographic data. The Knowledge Graph, queryable via API, spans billions of entities and a trillion-plus facts refreshed from continuous crawling.
Together these enable market intelligence, enrichment, news monitoring, and research at scale, all delivered as clean structured data for developers to integrate.
Developers, data engineers, and data-driven teams needing automatic structured extraction or entity intelligence at web scale, including market intelligence, sales enrichment, and research use cases.
Developers and data engineers integrating extraction APIs and Knowledge Graph queries.
Engineering, data, and product leaders funding web-data or enrichment infrastructure.
Technical evaluators, data-science teams, and market-intelligence practitioners.
A technical team needing automatic, web-scale structured extraction or entity intelligence, comfortable with API-driven, credit-based tooling.
Diffbot raised approximately $12.5M total, including a $10M Series A in 2016 led by Tencent and Felicis Ventures, with Bloomberg Beta among earlier investors. Figures per public reporting; verify with the company.
It uses computer vision and machine learning to recognize page structures (articles, products, discussions), so it can parse pages it has never seen into structured JSON automatically.
It is a machine-built graph of over 10 billion entities and more than a trillion structured facts, continuously refreshed from crawling the public web and queryable via API.
Yes. Diffbot offers a free tier with a limited number of credits and rate limits so you can evaluate the extraction APIs and Knowledge Graph.
Pricing is credit-based, and heavy usage, especially Knowledge Graph queries that cost many credits each, can add up quickly at scale.
Not really. It is a developer-first, API-driven platform. Non-technical users typically need engineering help or a no-code layer on top.
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