SignalFire Bet On AI Before It Was Cool And Now It Has $1B To Spend

When Chris Farmer founded SignalFire in 2013, his thesis was simple but radical: venture capital was ripe for disruption not by new partners or geographies, but by machine learning. At a time when most investors still leaned on gut instinct and Rolodexes, Farmer was betting on code. A decade later, that bet is paying off.

SignalFire just announced over $1 billion in new capital across multiple funds, its largest raise to date. That brings total assets under management to more than $3 billion. The fresh capital includes $200 million for pre-seed and seed, $500 million for breakout-stage companies, and $700 million in follow-on funding. The firm plans to deploy this across 100+ pre-seed and 60+ seed investments over the next 2.5 years, with check sizes ranging from $100,000 to $30 million.

From ML Thesis to Institutional Validation

Farmer, who previously led seed at Bessemer and was a general partner at General Catalyst, launched SignalFire with the idea that venture firms should look more like tech companies. The firm’s early iterations of Beacon tracked startup employee movements and market anomalies. Today, it’s evolved into a full-stack ML platform analyzing over 100 public data sources, spanning 495 million job profiles, 80 million companies, and 100+ metrics per company.

That platform doesn’t just notify investors when a founder is about to leave a unicorn. It flags red flags in GTM motion, predicts breakout potential, and integrates directly with portfolio company workflows. The firm says this gives it “a compounding edge,” and LPs seem to agree. Among the new backers is CalPERS, the largest pension fund in the United States, which made a rare $100 million commitment to SignalFire’s new fund.