Bridging the Gap Between
Artificial Intelligence & Human Logic.
We are a distributed team of mathematicians, physicists, and software engineers dedicated to solving the “Black Box” problem in educational AI.
The Origin Story
In late 2023, our founder Dr. Adrian Vance was grading calculus midterms when he noticed a strange pattern: students were making “confident errors”—hallucinating mathematical theorems that didn’t exist, but sounded plausible.
Tracing the source, he realized they were using Large Language Models (LLMs) to study. These models treated math like poetry—predicting the next word rather than calculating the logic.
MathAISolver was born from a simple thesis: Students need a tool that understands context like an LLM but calculates like a supercomputer. We built the Axiom-1 Engine to be that hybrid solution.
Prototype Phase
First CAS integration with GPT APIs. 45% accuracy rate.
Axiom-1 Engine Launch
Custom Neural Parser + SymPy Core. 98% accuracy rate.
Global Scaling
Visual Graphing, Handwriting OCR, and Tutor Integration.
Meet the Architects
Dr. Adrian Vance
PhD, COMPUTATIONAL PHYSICS
Former researcher at CERN. Obsessed with formal verification and symbolic logic systems.
Yuki Tanaka
MSc, AI SYSTEMS
Ex-Google Brain engineer. Architect of the Neural Semantic Parser module for Axiom-1.
Marcus Thorne
HEAD OF PEDAGOGY
20 years of teaching AP Calculus. Ensures the AI explains “Why”, not just “What”.
Our Core Philosophy
We believe that AI should be a tool for empowerment, not a crutch for laziness. Our algorithms are designed to foster understanding, transparency, and data sovereignty.
View Technical MethodologyPrivacy First
We don’t train our models on your homework. Your data is ephemeral.
Scientific Rigor
We prioritize accuracy over speed. No approximations where precision is required.
Open Access
Core features will always be free for students worldwide.