Logical Intelligence
Category: Foundation Models / LLMs
A frontier AI research lab developing non-autoregressive, energy-based reasoning models (EBMs) designed to achieve mathematical certainty and logical consistency beyond the capabilities of traditional LLMs. Logical Intelligence was founded in 2025. The company is led by Eve Bodnia. Based in San Francisco, USA. Team size: 10-50. Total funding raised: Undisclosed. Latest round: Seed. Key investors include Cathay Innovation, C Entrepreneurs, Pebblebed, Roar Ventures.
- Founded
- 2025
- Headquarters
- San Francisco, USA
- Team size
- 10-50
- Total funding
- Undisclosed
Value proposition
Eliminates the 'probabilistic guessing' and hallucinations inherent in autoregressive token prediction by using energy-based constraints to ensure verifiable reasoning and formal correctness.
Products and solutions
Kona 1.0 (Energy-based reasoning model / EBRM, alpha; pilots in energy, manufacturing, semiconductors), Aleph / Aleph Prover (agentic formal verification and Lean proof system; enterprise use), Token-free / non-autoregressive general reasoning framework, Formal verification for code, mathematics, and hardware correctness
Unique value
The company is one of the few frontier labs successfully pivoting away from the industry-standard Transformer/Autoregressive architecture toward Energy-Based Models (EBMs), led by a 'dream team' of Turing and Fields Medal winners.
Target customer
Enterprise developers of critical systems, formal verification engineers, academic research institutions, and industries requiring high-stakes mathematical accuracy (e.g., aerospace, cryptography, and quantitative finance).
Industries served
Artificial Intelligence, Software Engineering (Formal Methods), Mathematics & Scientific Research, Quantum Information Science, Cybersecurity
Technology advantage
Proprietary Kona EBM enforces mathematical constraints rather than next-token prediction; Aleph/Aleph Prover leads formal-reasoning benchmarks (PutnamBench 99.4% / 668 of 672 Lean proofs; VeriSoftBench 94%; Verina 100%), far above prior 76% Putnam figure and standard LLMs on formal logic.
How they differentiate
Utilizes non-autoregressive Energy-Based Models (EBMs) to enforce mathematical constraints and logical certainty, eliminating the 'probabilistic guessing' and hallucinations common in traditional Transformer-based LLMs.
Main competitors
OpenAI, Google DeepMind, Harmonic
Key partnerships
Harvard Center of Mathematical Sciences and Applications (CMSA), UC Santa Barbara (Quantum Information research ties), AMI Labs (collaboration intent via Yann LeCun)
Notable customers
Harvard Center of Mathematical Sciences and Applications (CMSA), Formal Verification Engineers
Major milestones
Appointed Yann LeCun as Founding Chair of Technical Research Board (Jan 2026), Launched Kona 1.0 energy-based reasoning model and public Sudoku demo (Jan 2026), Aleph reached 99.4% on PutnamBench (668/672 Lean proofs, Jan 2026), Aleph Prover SOTA across PutnamBench, VeriSoftBench, LeanEval; 100% Verina (May 2026), Fields Medalist Michael Freedman as Chief Science Officer; Alex Fetisov as CTO
Growth metrics
Aleph/Aleph Prover at 99.4% PutnamBench (668/672); #1 on VeriSoftBench (94%) and LeanEval; 100% Verina; Kona 1.0 in pilots (energy, manufacturing, semiconductors); leadership includes Turing Award winner and Fields Medalist.
Market positioning
Frontier AI research lab focused on formal verification and high-stakes reasoning for critical systems.
Geographic focus
North America (San Francisco), Global Research
Patents and IP
No registered patents disclosed; currently operating on proprietary research and trade secrets related to non-autoregressive architectures.
About Eve Bodnia
Eve Bodnia is a mathematician and physicist with a PhD in Quantum Information and Algebraic Topology from UC Santa Barbara. She studied under 2025 Nobel laureate Michel Devoret. Bodnia has authored over 20 academic papers on dark matter, quantum mechanics, and particle physics. Prior to founding Logical Intelligence, she conducted research at the intersection of geometry and machine learning and hosted high-level academic workshops at Harvard's Center of Mathematical Sciences and Applications (CMSA).
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Official website: https://logicalintelligence.com
