Thirteen years ago, when Chris Farmer founded SignalFire, an early-stage venture company in data analysis at the core of his investment strategy, many were skeptical of his approach. Traditional wisdom has determined that early companies do not have enough data to make their investment algorithms effective.
“This was a very radical idea and everyone thought I was crazy,” Farmer (pictured above, on the right, CTO and partner Ilya Kirnos) told TechCrunch.
There have been a lot of changes since Signalfire raised its first $53 million fund 2015. Today, more venture companies are adopting data-driven strategies in addition to, or sometimes instead of, traditional VC methods that rely on networking.
In fact, some venture companies today claim to be using AI to raise transactions, even having a private market focused on selling analytical tools that help investors of all kinds of things do “qualitative hard work.”
Still, Farmers find SignalFire’s approach unique. Because unlike other VCs using data, his company integrates AI into all aspects of the investment process.
And its limited partners seem to agree that their investment methods will continue to hone their advantage. On Monday, SignalFire said it had secured more than $1 billion in fresh capital and raised its managed assets to about $3 billion. This is the largest funding distance for a company that raised over $900 million, raised two years ago.
When many venture companies are forced to cut fund size, Farmer says raising such large funds means Signalfire is “less than the level of proof of concept to the established manager phase.”
The company’s new LPS includes a massive pension scheme, insurable banks and Asian sovereignty, farmers said. In fact, Calpers, the largest pension fund in the United States, reportedly committed SignalFire to Signalfire for the first time.
According to Farmer, the key reason some of the world’s biggest institutional investors were excited to support his company is that it focuses on seeds and pre-seed startups.
Given its size and inherent bureaucracy, a huge LPS prefers to write large checks on established companies that are expected to last. “Most seed funds are small. They have some great funds, so they’re done,” he said. “It’s very difficult for a large institution to back up such companies.”
Farmer claims Signalfire allows huge investors to make the most of both worlds. It’s about touching a very young startup on the scale you need.
The company’s point of entry into startups is in the pre-seed and seed stages, but the model is to continue investing in the company during its growth by using huge funds. Of course, this strategy isn’t that different from most multi-stage companies, except that most of these investors tend to focus more on the first supporters of Series A.
“We used scales to overtake everyone in the seeds,” Farmer said. Signalfire said it invested $100 million in some companies. Such capital is not readily available to most seed-focused companies.
Farmer said the model helped identify trends before competitors, despite having few key exits. He points to early investments in startups such as Grammarly, which was last valued at $13 billion. Grow Therapy raised a $88 million Series C from Sequoia last year. It also includes AI software for personal injury lawyers worth over $1 billion.
For this new funding, the company plans to continue investing in sector-specific AI startups, including healthcare and pharmaceuticals, consumers, infrastructure, developer tools and cybersecurity.
Despite the AI focus, SignalFire intentionally avoids companies building the foundational layer of AI models.
“I think a lot of venture dollars that enter model builders are at a great risk. They are jumping around every few weeks by another model. I don’t know if that’s defensive or not,” he said.
On the contrary, Signalfire tries to invest in companies that cannot easily replicate their business model or technology. “Evenup has no competitors. I like deep, deep, deep defensiveness,” says Farmer.
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