December 2, 2023

Six years ago, Yiğit Ihlamur, a former senior program manager at Google, observed that artificial intelligence was surpassing human capabilities in certain areas—or so he reckoned. With this perspective in mind, he studied various fields with the goal of solving a problem that he could spend the rest of his life grappling with.

“At an abstract level, I’m interested in the idea of ​​accelerating innovation that creates new products, services and experiences that were previously unimaginable,” Ihlamur told TechCrunch in an email interview. “I thought funding innovation was a math problem and started writing code and hacking.”

Ihlamur decided to focus on the venture capital space, which he believes is lagging behind in harnessing automation and artificial intelligence.With the help of several co-founders, he launched sail partnerwho described a venture capital firm as “AI-driven” and “product-led.”

Vela is an early-stage venture capital firm that manages $25 million and 32 portfolio companies, including self-checkout startup Grabango and robotics company Bear Robotics. Like all venture capital firms, Vela identifies (using in part predictive algorithms) new investment areas as it attempts to identify trends, find suitable opportunities, and eliminate threats to its existing investments.

To train its predictive algorithms, Vela draws on data from websites and social networks, as well as paid datasets like Crunchbase.

“Vela provides market intelligence and insights into innovative ideas; so technology decision makers can decide which tools to buy or build to grow their core business,” said Ihlamur. “Models must be informative and interpretable. Ultimately, our approach combines AI with expert heuristics.”

Of course, algorithms inevitably amplify bias in their training data—and this could have major implications for the VC a experiment In November 2020, Harvard Business Review (HBR) found that an investment recommendation algorithm tended to choose white entrepreneurs over entrepreneurs of color, and was more willing to invest in startups with male exposed A similar problem exists with CB Insights’ Mosaic tool, which uses indicators such as race, socioeconomic status, gender and disability to determine a person’s likelihood of success.

Ihlamur dodges questions about bias somewhat, acknowledging that it comes from the territory — but not necessarily offering a solution.

“A model can learn from other VCs’ biases or past biases,” he said. “First, there is a need to understand the root causes of these behaviors in risk markets. Second, each problem is unique and a general approach cannot be applied to all problems.”

Bias issues aside, Bay Area-based Vela isn’t the first to develop algorithmic tools to inform its investment decisions. Venture capital firms including SignalFire, EQT Ventures and Nauta Capital are using artificial intelligence platforms to flag potential top picks.

What sets Vela apart, according to Ihlamur, is that its “game-like” terminal is designed to help entrepreneurs, limited partners, and other venture capital firms use its services. Entrepreneurs can analyze trends in developer ecosystems like Amazon Web Services and GitHub, while whitelisted VCs can (with luck) spot promising seed-stage startups, and LPs can ask Vela why it invested in a particular startup. company problems.

Vela’s GitHub repository (including its algorithmic models) is public – for inspection and reuse.

“While some VCs may be experimenting with AI-based sourcing, we haven’t seen any VCs taking a product-led approach,” Ihlamur said. “Anyone can go to Vela’s website and use our product. We are building relationships with entrepreneurs and LPs programmatically – our ultimate goal is to have AI and automation touch and manage every aspect of our business .”

This is a method that has worked well for Vela so far. The company claims to be at “breakeven,” leading or co-leading check sizes of $500,000 to $1.5 million.

In the near term, Vela plans to invest primarily in artificial intelligence, data, and developer-focused startups. Ihlamur specifically expressed enthusiasm for generative artificial intelligence, a market that could be worth $51.8 billion by 2028 — depending on Which sources do you trust.

“Like many other venture capital firms, the pandemic has had a positive impact on our business,” Ihlamur said. “The launch of OpenAI’s ChatGPT provides further tailwinds for us as an AI-driven venture capital firm … Regarding the broader slowdown in the technology space, we are not worried because we are at breakeven as a company status and has capital investment. Despite the economic slowdown, there are still plenty of opportunities that can be partially captured due to the rapid development of artificial intelligence.”