Symbolica AI builds symbolic, structured AI models and a toolkit for creating and pre-training models tailored to tasks such as code generation and proving mathematical theorems. The 16-person team launched out of stealth and intends to sell bespoke structured models and state-of-the-art code synthesis models to large enterprise customers, while possibly offering consulting and support. Founder George Morgan, an ex-Tesla engineer, argues these models achieve greater accuracy with lower data requirements, lower training time, lower cost and provably correct structured outputs compared with scale-focused deep learning. Symbolica positions its approach as marrying mathematical abstractions with neural networks to improve reliability, transparency and accountability and to enable formal reasoning capabilities over large codebases. The company disclosed a $33 million investment earlier this year led by Khosla Ventures, with Abstract Ventures, Buckley Ventures, Day One Ventures and General Catalyst participating. Symbolica is San Francisco-based and plans to double staff by 2025.

Total raised

$33M

Funding rounds

1

Latest round

Equity

Latest activity

Apr 2024