Thirteen years ago, Chris Farmer established SignalFire, an early-stage venture firm emphasizing data analysis in its investment strategy. Initially, many were doubtful about this approach, as conventional wisdom suggested that early-stage companies lacked sufficient data for effective investment algorithms.
“This was a very radical idea, and everyone thought it was crazy,” Farmer, who was photographed alongside CTO and partner Ilya Kirnos, remarked to TechCrunch.
Since SignalFire raised its first $53 million fund in 2015, the venture capital landscape has evolved significantly. More firms now incorporate data-driven strategies alongside, or even in place of, traditional methods reliant on networking.
Today, several venture firms claim to use AI for deal sourcing, and some private market-focused companies offer analytical tools to aid all kinds of investors in conducting “qualitative diligence.”
Still, Farmer believes SignalFire’s approach is unique due to its comprehensive integration of AI throughout the investment process — from identifying promising early-stage startups to assisting portfolio companies with recruiting and product marketing.
SignalFire’s limited partners seemingly share this sentiment, as the firm recently announced it has secured over $1 billion in new capital, raising its total assets under management to approximately $3 billion. This represents SignalFire’s largest funding achievement to date, surpassing the $900 million it raised two years prior.
At a time when many venture firms have been compelled to reduce their fund sizes, Farmer suggests that securing such a large fund indicates SignalFire has moved beyond the proof-of-concept phase to become an established manager.
The firm’s new limited partners include major pension plans, insurers, banks, and an Asian sovereign. Notably, CalPERS, the largest pension fund in the U.S., has reportedly committed $100 million to SignalFire for the first time.
Farmer attributes part of the appeal for some of the world’s largest institutional investors to SignalFire’s focus on seed and pre-seed startups. Giant limited partners, due to their size and inherent bureaucracy, prefer to make large investments in established firms expected to endure. “Most seed funds are small. They have a few great funds, and then they’re done,” he explained. “It’s very hard for big institutions to back firms like that.”
With SignalFire, large investors reportedly have the opportunity to gain exposure to very young startups while benefiting from the scale and longevity they require.
Although SignalFire initially invests in startups at the pre-seed and seed stages, its model leverages its substantial fund to continue investing as these companies grow. This strategy distinguishes it from most multi-stage firms that typically focus on backing companies at Series A.
“We use our scale to outgun everyone at the seed,” Farmer stated, noting that SignalFire has invested $100 million into some companies, a level of funding not commonly available to most seed-focused firms.
According to Farmer, despite having few significant exits, SignalFire’s model has enabled it to identify trends ahead of its competitors. The firm has made early investments in startups like Grammarly, last valued at $13 billion, Grow Therapy, which raised an $88 million Series C from Sequoia last year, and EvenUp, an AI software for personal injury lawyers worth over $1 billion.
For its new set of funds, SignalFire plans to continue investing in sector-specific AI startups, covering areas like healthcare and pharma, consumer products, infrastructure and developer tools, and cybersecurity.
Despite its AI focus, SignalFire intentionally avoids companies building foundational AI model layers.
“I think that many venture dollars going into model builders are at a massive risk. They’re getting leapfrogged every couple of weeks by another model. You don’t know whether it’s defensible,” Farmer remarked.
Conversely, SignalFire seeks to invest in businesses whose models or technology cannot be easily replicated. Farmer emphasized the preference for ventures with deep defensibility, citing EvenUp as an example of a company without competitors.
