Axiomatic AI offers Lemma, an AI co‑explorer that combines large‑language‑model reasoning with formal proof systems to deliver mathematically verified results for engineering and scientific problems. The platform supports photonics, electronics, thermal, mechanics, and signal domains, outputting code‑enabled Marimo notebooks that can be run locally, via MCP, or integrated into GitHub workflows, ensuring provably correct calculations and eliminating AI hallucinations.
Funding
Funding not disclosed
Founders
Product
Problem
Engineers and scientists often rely on AI-generated calculations and simulations that can produce unverified or approximate results, leading to costly errors in photonics, electronics, thermal, mechanical, and signal design. The lack of formal verification makes it difficult to trust AI outputs for mission‑critical engineering workflows.
Solution
Axiomatic AI’s Lemma platform combines large‑language‑model reasoning with formal proof systems to provide mathematically rigorous, verifiable results for engineering and scientific problems. Users interact with Lemma through an AI co‑explorer that can derive, validate, and analyze equations across mathematics, physics, and engineering domains. Every output is checked against formal specifications, ensuring correctness before results are returned and eliminating hallucinations. Verified results are delivered in interactive Marimo notebooks, allowing code inspection, execution, and seamless integration into existing workflows. Lemma can be run locally, via the MCP framework, or as a GitHub integration, and works with popular editors such as Claude Code and Cursor.
Target Audience
Primary customers are R&D engineers, computational scientists, and product development teams that require provably correct AI assistance for design, analysis, and verification of complex physical systems.
Features
- Formal proof‑backed computation that guarantees mathematical correctness of AI‑generated results
- Multi‑domain support for photonics, electronics, thermal, mechanics, and signal processing problems
- Interactive Marimo notebook output enabling editable, executable code alongside verified results
- Integration with MCP, local execution, and GitHub workflows for flexible deployment
- Compatibility with Claude Code, Cursor, and other MCP‑compatible editors for low‑code usage
- Benchmark‑proven performance, outperforming leading AI systems on theorem‑proving and formal reasoning tasks