A massive valuation for a research lab
I view the $32 billion valuation reached in April 2025 as a massive bet on Ilya Sutskever’s research vision. After the initial $1 billion Series A in September 2024 set a $5 billion valuation, the company secured an additional $2 billion via a round led by Greenoaks Capital Partners. This April 2025 investment included participation from Alphabet and NVIDIA. The founding trio, Ilya Sutskever, Daniel Gross, and Daniel Levy, established the firm to develop safe superintelligence. Daniel Gross, who formerly served as a partner at Y Combinator and led AI efforts at Apple after selling his startup Cue, serves as CEO. Daniel Levy also comes from OpenAI, where he worked as a researcher and member of the technical staff. The original Series A funding, which consisted entirely of cash rather than cloud credits, included investors such as Andreessen Horowitz, Sequoia Capital, DST Global, and SV Angel. The investment partnership NFDG, run by Nat Friedman and Daniel Gross, also participated in that initial round. This capital helps the company acquire massive computing power and recruit top-tier engineers. The group’s work targets the development of artificial general intelligence, a system capable of performing any intellectual task a human can.
| Metric | Value |
|---|---|
| Total Capital Raised | $3 billion |
| April 2025 Valuation | $32 billion |
| September 2024 Valuation | $5 billion |
| Current Staff Count | ~20 employees |
Scaling in peace without commercial pressure
The company pursues a strategy called "scaling in peace" to ensure safety stays ahead of capabilities. This philosophy differs from OpenAI, where Sutskever served as chief scientist before his May 2024 departure. While OpenAI reported $50 billion in revenue in October 2026 and reached an $852 billion valuation in March 2026, SSI focuses on long-term research. Sutskever defines safety like nuclear safety rather than the trust and safety protocols seen in enterprise models. You already know that OpenAI and Anthropic compete fiercely, but SSI avoids the pressure of product cycles. The team aims to advance capabilities while ensuring safety remains a technical priority through engineering breakthroughs. This strategy follows internal tensions at OpenAI regarding the balance between safety priorities and rapid commercialization, which led to the departure of safety lead Jan Leike. This departure is a significant point in the competition for talent between companies like OpenAI and Anthropic. The company’s secretive operations and lack of public outputs make its technical differentiation difficult to verify. The competition in the field remains intense, as OpenAI raised $122 billion in a single round in March 2026. Sutskever has suggested that current large language models have fundamental limitations compared to human cognition, particularly in generalization abilities. This belief drives the search for breakthroughs beyond simply training ever-larger models on ever-more data.
A lean team for a massive goal
The company operates with a lean, cracked team of 20 engineers and researchers split between offices in Palo Alto, California, and Tel Aviv, Israel. This small group receives all $3 billion in total funding to secure computing power and attract talent. Daniel Gross, who previously led AI efforts at Apple, serves as CEO. Unlike OpenAI, which reported $50 billion in revenue in October 2026, SSI generates no revenue. The company’s business model prevents the distraction of management overhead or product cycles, as the founders intend to focus all resources on fundamental research rather than chasing the competitive rat race of commercial deployment. The organization leverages deep roots in both Palo Alto and Tel Aviv to recruit the best minds in the field. The founders describe the mission as building the world’s first straight-shot SSI lab with one goal and one product. The team seeks to build a system capable of performing any intellectual task a human can, while ensuring it stays safe and aligned with human goals. The team aims to solve the technical problems associated with both safety and capabilities through revolutionary engineering and scientific breakthroughs. How will a team of 20 people actually outpace the massive engineering armies at Google or OpenAI?
