Deep Intelligent Analysis of Financing News and Automated Company Research Workflow
This workflow automatically scrapes financing news from major technology news websites, accurately filters and extracts key information such as company names, financing amounts, and investors. It combines various AI models for in-depth semantic analysis, providing detailed company backgrounds and market analysis. The research results are automatically stored in an Airtable database for easy management and subsequent analysis, helping venture capitalists, researchers, and business decision-makers to access industry trends in real-time, thereby improving decision-making efficiency and information value.
Workflow Name
Deep Intelligent Analysis of Financing News and Automated Company Research Workflow
Key Features and Highlights
This workflow automatically crawls the latest financing news from leading technology news websites such as TechCrunch and VentureBeat. It precisely filters articles containing keywords like “raise,” extracting and structuring critical information including company name, funding round, amount raised, investors, and market sector. Leveraging multi-model deep semantic analysis (incorporating Anthropic Claude, Perplexity AI, and JINA Deep Search), it performs company website lookups, detailed background research, and business model analysis. The research results are then automatically stored in an Airtable database, enabling efficient management and subsequent analysis.
Core Problems Addressed
- Automates the acquisition and filtering of vast amounts of tech news to extract financing-related key information, eliminating tedious manual searches.
- Accurately parses unstructured news text to extract multi-dimensional financing and company data, ensuring data accuracy and completeness.
- Deeply integrates multiple AI models for intelligent analysis to supplement company background, market positioning, and business model insights, enhancing information value.
- Synchronizes data in real-time to an enterprise-grade database, facilitating data management, sharing, and driving business decisions.
Application Scenarios
- Venture capital firms or investment analysts tracking industry financing trends in real-time to improve investment decision-making efficiency.
- Corporate strategic planning departments conducting competitor and market analysis to identify industry hotspots and potential collaboration opportunities.
- Financial data service providers automating the collection and organization of financing information to enrich data product offerings.
- Research institutions and media editors quickly accessing authoritative financing news and in-depth company background materials.
Main Workflow Steps
- Fetch News RSS/Sitemaps: Retrieve news sitemaps (in XML format) from TechCrunch and VentureBeat via HTTP requests.
- Parse and Split Article Lists: Convert XML data to JSON and split it into individual article records.
- Keyword Filtering: Filter financing-related news articles containing “raise” in the title or URL.
- Fetch Full Articles: Obtain complete HTML content of the filtered articles through HTTP requests.
- HTML Content Parsing: Extract article titles and plain text body using CSS selectors.
- Merge Multi-Source Data: Combine articles from different sources into a unified dataset.
- Structured Information Extraction: Use Anthropic Claude 3.5 model to extract key details such as company name, funding round, amount, investors, and market sector.
- In-Depth Company Research: Invoke Perplexity AI and JINA Deep Search models to perform company website lookups and conduct detailed background and business analysis based on extracted information.
- Data Cleaning and Transformation: Automatically correct and structurally parse complex JSON data to ensure data standardization.
- Write to Airtable Database: Store the final structured financing and company research data into designated Airtable tables for easy querying and management.
- Support Sub-Workflow Invocation: Enable flexible extension and reuse through “Execute Other Workflow” nodes.
Systems and Services Involved
- TechCrunch & VentureBeat: Primary sources of technology financing news.
- HTTP Request Nodes: For fetching news data and webpage content.
- XML and HTML Parsing Nodes: For data conversion and content extraction.
- Filter Nodes: Keyword-based filtering of financing-related articles.
- Langchain-Integrated AI Models: Anthropic Claude 3.5, Perplexity AI (via OpenRouter), and JINA Deep Search for natural language understanding and information extraction.
- Airtable: Platform for structured data storage and management.
- Built-in n8n Nodes: Including manual triggers, splitting, merging, variable setting, and other fundamental nodes.
Target Users and Value Proposition
- Venture Capitalists and Investment Analysts: Automatically obtain the latest financing information to support investment decisions.
- Corporate Strategy and Market Researchers: Access competitor financing dynamics and conduct in-depth research.
- Financial Data Service Providers: Automate the collection and structured management of financing news.
- Tech Media Editors and Content Teams: Quickly filter and deepen reporting content.
- Product Managers and Automation Engineers: Build intelligent data acquisition and analysis pipelines to enhance work efficiency.
By integrating multi-source data fusion with cutting-edge AI technologies, this workflow significantly enhances the monitoring of financing news and company research efficiency, enabling users to stay abreast of industry funding trends in real-time and driving more precise business insights and decision support.