As AI tools become more common in education, the question is no longer only whether they can produce an answer, but how reliably they can reason through one. That question sits at the center of GPAI’s latest India push, after the South Korean AI startup backed by OpenAI demonstrated solutions equivalent to a score of 351 out of 360 on JEE Advanced 2025 problems.
JEE Advanced is among the toughest undergraduate entrance examinations in the world, built around multi-step physics, chemistry and mathematics problems that demand deep conceptual understanding. GPAI says its performance reflects a reasoning system that goes beyond surface-level response generation and instead uses Structured Chain-of-Thought techniques to break complex problems into smaller logical units before reconstructing a coherent solution.
That approach matters because STEM problems often require more than a correct final answer. They demand a transparent path from premise to conclusion, especially in subjects where one wrong assumption can derail the full solution. GPAI says its system is designed around that idea, combining large language model reasoning with a deterministic computational engine to create answers that are both structured and verifiable.
The company’s visual reasoning capability is also part of the story. GPAI says it can interpret images, use visuals during reasoning and synthesize high-precision diagrams during inference, which is especially useful in mechanics, optics and calculus, where diagrams often carry the logic of the problem itself.
This multimodal approach is one reason the startup says it is gaining attention beyond its home market. GPAI says it is used by researchers and students across the US, Europe and Asia, with especially strong adoption in India’s STEM ecosystem, including IITs. The company claims that within three months of launch, it had acquired a large number of IIT users, including more than a thousand at IIT Delhi alone.
The same reasoning-first positioning is also reflected in Turing’s U.S. adoption update, which says GPAI is now used at 415 U.S. universities and that its visualizer can produce diagrams and charts at a research-ready standard for journal submissions and slide decks . The release also highlights users at MIT, Stanford, Harvard and UC Berkeley, underscoring how the product is being framed around serious STEM workflows rather than casual chat use. GPAI is also positioning additional features that support academic workflows. Its visualizer technology is built to generate publication-ready diagrams and editable figures, while its handwritten solution analysis tool can annotate and grade user responses. The company’s problem-generation technology is designed to create complex variants of existing problems while preserving the original logic and flow.
The larger message is straightforward: GPAI wants to be seen as a research-led STEM AI platform, not just another study assistant. By combining deterministic logic, Chain-of-Thought reasoning and visual problem solving, the company is trying to show that the future of education AI will depend on explainability and rigor as much as speed.
