How does Diffbot differ from traditional web scrapers?

Diffbot uses AI to auto-detect page structure, eliminating the need for CSS selectors or XPath rules. It also provides a pre-built Knowledge Graph with direct access to 246M organizations and 1.6B articles.

What data types are in the Knowledge Graph?

Covers organizations (246M with revenue, locations), news articles (1.6B), retail products (3M), forum discussions, and events (23k). All data supports on-demand extraction and updates.

How does Diffbot pricing work?

Pricing is not public; contact sales for details. Free trial available with full API access.

What are common use cases?

Market research, competitive analysis, risk assessment, news aggregation, and CRM enrichment for teams needing large-scale web data. Popular in finance, consumer, news, and risk sectors.

Diffbot

Diffbot automates web data extraction using AI and Knowledge Graph. Access 246M organizations, 1.6B articles, products, and discussions. No coding rules required.

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Summary

Diffbot is an AI web data extraction platform that transforms website content into structured data. It solves unstructured web data integration challenges through Knowledge Graph and automated crawling.

What is Diffbot?

Diffbot uses AI, computer vision, and machine learning to automatically extract data from any website without writing rules. The platform offers a Knowledge Graph covering 246M organizations, 1.6B articles, 3M retail products, and forum discussions, supporting on-demand extraction and data enrichment.

Core Capabilities

Knowledge Graph search & enrichment: Find and enrich organization, people, and news data
Automated web extraction (Extract): Analyze articles, products, discussions without rules
Site crawling (Crawl): Quickly turn websites into structured databases
Natural language processing (NLP): Infer entities, relationships, and sentiment from text
Multi-data type support: Organizations (50+ fields), news, products, events, discussions

Pros

No crawling rules needed: AI auto-detects page structure
Massive Knowledge Graph: Pre-built 246M organizations, 1.6B articles
Real-time extraction & updates: Pull latest web data on demand
Deep data fields: Company revenue, locations, investments; product reviews, pricing
Entity matching & sentiment analysis: Beyond plain text extraction

Cons

Pricing transparency lacking: Must contact sales for costs
Learning curve: Knowledge Graph and API require time to master
Data coverage gaps: Some verticals (e.g., events with only 23k records) have limited data
Reliant on page structure: Dynamic or non-standard sites may affect accuracy

Decision Guidance

Use when: You need large-scale web data extraction for market research, risk assessment, news aggregation, or CRM/database enrichment. Knowledge Graph suits teams needing pre-built organization and news data fast.

Consider alternatives: For small-scale scraping or tight budgets, traditional tools (Scrapy, Apify) may be more economical. For vertical-specific data (e.g., LinkedIn contacts), specialized data providers may offer better precision.