To get a roundup of TechCrunch's biggest and most important stories delivered to your inbox every day at 3 p.m. PDT, subscribe here. Hello and welcome to Daily Crunch for June 9, 2021. Today was TC Sessions: Mobility, a rollicking good time and one that we hoped you enjoyed. Looking ahead, we're starting to announce some speakers for Disrupt -- including Accel's Arun Mathew. Mark your calendars, Disrupt is going to be epic this year.
SignalfFire, a six-year-old, San Francisco-based venture firm that prides itself on mining what it says is more actionable data about, well, the world, has just raised a pair of funds that total $500 million in capital commitments. One of the vehicles is a $200 million "seed" fund that SignalFire will use to write checks up to $5 million in nascent startups; the other is a $300 million fund designed to invest in those of the firm's portfolio companies that are beginning to pull away from the pack and need growth-stage funding. Both are a major step up for the young firm, which closed its debut fund with $53 million in 2015 before raising $330 million in capital across two funds in 2017. According to firm founder Chris Farmer -- who founded SignalFire after logging several years at both Bessemer Venture Partners and General Catalyst -- the firm also has many more people investing the money. Altogether, SignalFire now employs 30 people across an engineering and data science unit; a unit dedicated to portfolio operations; and a unit that does the actual venture investing.
Signalfire, hailing from San Francisco, is a self-described "most quantitative fund in the world" & "the only VC that brings a data platform to its portfolio companies". It is also the fund whose approach I find the most appealing. At the heart of its operations lies an end-to-end real-time data platform called Beacon, a sort of a Bloomberg terminal for startup industry or as Chris Farmer (CEO of Signalfire) describes it, "a proprietary mini-Google", powering the entire value chain of a venture -- from deal origination through picking the right investments, and deal syndication to portfolio support. Beacon tracks the performance of more than 6 million companies in real-time by drawing upon 10milion data sources, such as academic publications, patent registries, open-source contributions, regulatory filings, company webpages, sales data, appstore rankings, social networks, and even raw credit card data. Companies that are outperforming or doing something notable are flagged up on a dashboard, effectively allowing Signalfire to see deals earlier than traditional venture firms.
Imagine if you could analyze trillions of data points using machine learning algorithms to come up with a list of the absolute best startups to invest in. That's no small task as there are an estimated 23,000 startups in Silicon Valley alone. One startup called SignalFire is doing just that by taking unstructured data from over 2 million data sources and then using machine learning algorithms to pick the best startups to invest in. Wouldn't you be the least bit curious to know which companies they picked? We were extremely interested to know, so we had one of our on-staff PhDs take a look on Crunchbase and lo and behold, 8 startups were listed that SignalFire has invested in so far.
Give us your feedback Thank you for your feedback. One of the biggest challenges for venture capital companies is finding interesting investment targets before anyone else. It is often a laborious, travel-intensive job. But machine learning and predictive analytics are starting to transform how an investor puts a portfolio together. "My job used to be about getting on a plane once a week and going to a different European city to try to find people who were doing interesting things," says Roberto Bonanzinga, co-founder of InReach Ventures and previously a partner at Balderton Capital, a UK-based VC firm which invests primarily in early-stage European technology companies.