As AI becomes embedded in classrooms, concerns are rising that students may prioritise quick answers over deep understanding. Fermi, an AI-led edtech startup founded by former technology executive Peeyush Ranjan, aims to shift that balance by using AI to promote reasoning, problem‑solving and conceptual clarity rather than providing turnkey solutions.
Focusing on productive struggle, not shortcuts
Educators and researchers emphasise that authentic learning often requires productive struggle — grappling with problems to build durable understanding. Fermi’s design philosophy echoes this insight: its tutor intentionally avoids handing out final answers and instead offers prompts, hints and guided questions that nudge learners through the thinking process.
By foregrounding how students reason rather than simply what they submit, the platform seeks to reduce dependence on convenience-driven workflows such as copying chatbot responses and to strengthen long‑term retention and confidence.
STEM-first design and handwriting interface
Fermi’s initial product targets high‑school STEM subjects — mathematics, physics and chemistry — where stepwise reasoning and symbolic notation are central. A handwriting‑first interface lets students write equations, draw diagrams and solve problems with a stylus or touch input, closely mirroring traditional classroom methods.
This natural input model lowers the friction of interacting with AI: learners solve problems as they would on paper while the system observes, interprets and responds in real time, without requiring typed prompts or elaborate instructions.
Tools to support teachers
Recognising that AI should augment, not replace, instructors, Fermi includes a Classroom Command feature that provides teachers with actionable analytics. The tool surfaces learning patterns — which concepts students struggle with, common reasoning errors and where misconceptions emerge — enabling earlier and more targeted interventions.
In pilot programmes, these data‑driven insights helped teachers personalise instruction. Students who practiced more concept‑based problems showed progressively greater independence, relying less on hints as their understanding improved.
Pilot outcomes and early evidence
During initial trials spanning several dozen students over three months, participants attempted thousands of concept‑focused questions. Learners who began below expected performance levels demonstrated steady improvement, suggesting the reasoning‑led approach can produce measurable gains.
Teachers involved in the pilots reported higher classroom engagement and clearer visibility into student progress, reinforcing the value of combining formative analytics with guided practice.
India as a strategic market with global ambitions
While operating with a global outlook, Fermi considers India a priority market because of its large student population and strong demand for quality STEM instruction. The startup is running pilots across Indian schools alongside international trials, and plans partnerships with educational institutions to scale adoption.
Future plans include flexible pricing models for individual learners and schools, and an eventual expansion into college‑level and professional learning, while maintaining a core focus on responsible, human‑centred AI pedagogy.
By integrating classroom practices with AI that emphasises reasoning over rote answers, Fermi seeks to offer an alternative to answer‑centric learning and to support teachers in fostering deeper, more durable student understanding.
