Hi HN, I'm the creator of thinkercan. The best way to describe it is ChatGPT for reasoning + Photomath for the step-by-step solution. I built this because I wanted a tool that could understand a student's question in natural language (even word problems) like ChatGPT, but then generate a perfect, step-by-step mathematical solution like Photomath. The core problem with using LLMs alone for math is that you can't trust their process. They hallucinate steps and get the final answer wrong. My goal was to fix that. Under the hood, thinkercan uses an LLM as an intelligent interface to understand the query. But the crucial part is that it then calls a dedicated symbolic math engine to generate the entire solution path—every single step, from start to finish. This means you get a solution that is both easy to understand and mathematically sound from top to bottom. Here’s a 50-second video that shows the process: https://www.youtube.com/watch?v=nI05v-Yltyc We're still in the early stages (just added calculus support), and I'm here to answer any questions. I would be grateful for any feedback on the approach and the product.