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Axiom

Category: AI Safety

A 'Verifiable AI' platform that utilizes formal mathematical methods to prove the correctness and safety of AI-generated code, effectively eliminating hallucinations in mission-critical software development. Axiom was founded in 2025. The company is led by Carina Hong. Based in Palo Alto, USA. Team size: 11-50. Total funding raised: $264.0M. Latest round: Series A. Key investors include Menlo Ventures, B Capital, Greycroft, Madrona, Toyota Ventures, Triatomic Capital.

Founded
2025
Headquarters
Palo Alto, USA
Team size
11-50
Total funding
$264.0M

Value proposition

Transforms AI-driven code generation from a probabilistic 'best guess' into a deterministic, provably correct output, allowing companies to deploy AI-generated code in production with mathematical certainty.

Products and solutions

AxiomProver (Automated Formal Verification Engine), Lean-Integrated AI Coding Environment, Automated Proof Generation Pipeline, Enterprise Safety & Compliance Dashboard for AI Code, Axplorer (AI Pattern Discovery Tool for Mathematicians), AXLE (Public Proof Verification Engine)

Unique value

Axiom is the first to bridge the gap between Large Language Models (LLMs) and formal theorem provers like Lean at an industrial scale, moving beyond 'likely' code to 'provably correct' code.

Target customer

Enterprise software engineering departments, CTOs of mission-critical infrastructure, and organizations in highly regulated industries (Finance, Aerospace, Cybersecurity).

Industries served

Software Engineering, Cybersecurity, Financial Services, Aerospace & Defense, Critical Infrastructure

Technology advantage

Combines high-level neural network reasoning with symbolic logic; led by a team of world-class mathematicians and former Meta FAIR researchers who developed the AI Research SuperCluster.

How they differentiate

Axiom differentiates by utilizing formal mathematical verification (Lean theorem prover) to provide deterministic, provably correct code, whereas competitors rely on probabilistic LLM outputs that are prone to hallucinations.

Main competitors

Harmonic, Logical Intelligence, Math Inc

Key partnerships

Menlo Ventures (Series A Lead), B Capital (Seed Lead), Greycroft, Madrona, Toyota Ventures, Triatomic Capital, Academic collaborations (Stanford, MIT); EconLib with Scott Kominers / Harvard Business School

Notable customers

Enterprise Pilot Partners (Financial Services), Aerospace & Defense Contractors, Cybersecurity Firms

Major milestones

Raised $200M Series A at a $1.6B valuation (March 2026), Recruited world-renowned mathematician Ken Ono as Founding Mathematician, Produced Lean formalizations of Erdős Problems #124 and #481 via AxiomProver (Dec 2025; prior literature/priority contested), Developed industrial-scale bridge between LLMs and the Lean theorem prover, Released Axplorer open-source AI tool for mathematical pattern discovery (March 2026), Released AXLE public proof verification engine (March 2026), Launched EconLib formal economics library project with Scott Kominers (Fortune, June 2026), AxiomProver formalized BGP246 bounded prime-gaps theorem in Lean (Aug 2026), Announced improved bounded prime-gap bound of 212 with AxiomProver verification (Sep 2026)

Growth metrics

Reached a $1.6B valuation within one year of founding; team scaled to 40+ researchers and mathematicians (Fortune, Jun 2026).

Market positioning

High-end Enterprise AI Safety and Formal Verification specialist for mission-critical infrastructure.

Geographic focus

North America (Palo Alto based) with a global focus on enterprise software engineering markets.

Patents and IP

Proprietary algorithms for translating natural language/code into formal mathematical proofs (specific patent filings are typically maintained as trade secrets or are in 'pending' status during early-stage growth).

About Carina Hong

Carina Hong is a distinguished mathematician and former Stanford PhD student who dropped out to found Axiom. She graduated from MIT in three years with a double major in Mathematics and Physics, where she was awarded the Morgan Prize (the highest honor for undergraduate mathematical research in the US). She was a Rhodes Scholar at the University of Oxford and was pursuing a joint JD/PhD in Mathematics at Stanford before launching Axiom to solve the 'hallucination' problem in AI through formal verification.

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