Signal.nfx Scraper With Emails — Signal.nfx | Lagic

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Overview

Extract investor and founder profiles from Signal.nfx lists, capturing their investment thesis, portfolio companies, and social media links. Optionally, find verified email addresses for direct outreach and fundraising.

Signal by NFX is a widely used directory for discovering investors, founders, and promising startups. This tool allows you to extract the data from Signal's curated lists and turn it into a structured dataset for your own analysis and outreach. It's designed for anyone needing high-quality data on the key players in the startup ecosystem. Founders can use it to build targeted lists of investors who match their vertical and funding stage. Venture capitalists and scouts can map co-investor networks and identify individuals with a strong track record in a specific niche. M&A teams and sales professionals can source potential acquisitions or customers from investor portfolios. ### What You Get Each profile you extract contains a complete picture of the individual, including: * **Professional Background:** A full history of their education and work experience, including titles, companies, and schools. * **Investment Thesis:** Their preferred investment locations, check sizes (minimum, maximum, and target), and the role they typically take (e.g., lead investor). * **Network & Portfolio:** See which companies they've invested in, details about those funding rounds, and a list of their most frequent co-investors. * **Contact & Social Links:** Direct links to their LinkedIn, Twitter, AngelList, and Crunchbase profiles, plus their personal or company website. ### Find Emails for Direct Outreach A key feature of this tool is the ability to enrich profiles with email addresses. By enabling the email collection option, the tool will attempt to find a verified email for each person. You can even choose to include 'risky' emails, which are algorithmically determined but have a slightly lower confidence score. All emails are tagged, so you can easily filter between 'valid' and 'risky' results in your final dataset.