In India, limited resources, geographical constraints, and economic factors present barriers to quality higher education for some students.
A shortage of teachers, particularly in remote or low-income areas, makes it harder for students to receive the guidance they need to prepare for highly competitive professional and academic programs. Microsoft Research is developing new algorithms and techniques that are enabling Physics Wallah (opens in new tab), a growing educational company, to make its AI-based tutoring services more accurate and reliable, to better support students on their education journey.
As in other countries, many Indian students purchase coaching and tutoring services to prepare for entrance exams at top institutions. This includes offline coaching, where hundreds of students meet in a classroom staffed by teachers covering a structured curriculum. Online coaching enables students to learn remotely in a virtual classroom. Hybrid coaching delivers virtual lessons in a physical classroom.
Offline courses can cost as much as 100,000 Indian rupees a year—equivalent to hundreds of U.S. dollars. This puts them out of reach for many lower income students living in smaller and mid-sized Indian cities, as well as rural villages. Online courses are much more affordable. They allow students to work at their own pace by providing high-quality web-based content supported by teachers who work remotely.
Meeting this need is the mission of Physics Wallah. The company uses AI to offer on-demand tutoring at scale, curating volumes of standard science- and math-related content to provide the best answers. Some 2 million students use the Physics Wallah platform every day, at a fraction of the cost of offline tutoring. For example, its prep courses for the Joint Entrance Examination (JEE), which is required for admission to engineering and technology programs, and the National Eligibility cum Entrance Test (NEET), a required entrance exam for medical and dental school candidates, cost between 4,200 and 4,500 rupees per year. That’s roughly 50 U.S. dollars.
“The mantra here really is how do we provide quality education in an affordable manner and accessible to every student, regardless of who they are or where they come from.”
—Vineet Govil, Chief Technology and Product Officer, Physics Wallah
Microsoft Research India’s collaboration with Physics Wallah is part of a 20-year legacy of supporting emerging Indian companies, underscored by the January 2025 announcement that Microsoft will invest $3 billion (opens in new tab) in cloud and AI infrastructure to accelerate the adoption of AI, skilling, and innovation.
Physics Wallah has developed an AI-driven educational suite, Alakh AI, leveraging OpenAI’s GPT-4o model through Microsoft Azure OpenAI Service. Alakh AI’s flagship offerings include AI Guru and the Smart Doubt Engine, both designed to transform the learning experience in and beyond the classroom.
- AI Guru acts as a personal academic tutor, delivering adaptive guidance based on a student’s progress, real-time question-solving, and customized content that evolves with their learning journey.
- Smart Doubt Engine is an AI tool through which students can ask questions (also known as “doubts” in Indian English) during live classes and receive instant responses.
Additionally, the Alakh AI suite includes:
- AI Grader for subjective answer evaluation without human intervention
- Sahayak for crafting hyper-personalized learning paths tailored to individual students’ needs
This innovative ecosystem elevates learning efficiency and accessibility for students.
How does AI Guru work?
Let’s say a student had a question about Newton’s laws of motion, a core concept in physics. She would type her query into the AI Guru chat window (she could also just talk to it or upload an image from a textbook) and receive a text answer plus images derived from standard textbooks and curated content, typically in just a few seconds. AI Guru also provides a short video where a teacher offers additional context.
Getting the technology right
The Alakh AI suite is powered by OpenAI’s foundational models GPT-4 and GPT-4o, integrated with a retrieval-augmented generation (RAG) architecture. It leverages Physics Wallah’s rich repository of high-quality curated content—developed and refined over several years—along with continuous updates from subject matter experts to ensure new materials, textbooks, tutorials, and question banks are seamlessly incorporated. Despite considerable progress, the existing AI sometimes falters when navigating complex academic problems.
“The accuracy level of today’s large language models (LLMs) is not up to the mark where we can provide reliable and satisfactory answers to the students all the time—specifically, if it’s a hard mathematical problem involving complex equations,” Govil said.
That’s one important focus of the collaboration. Researchers from Microsoft Research are developing new algorithms and techniques to enhance the accuracy and reasoning capabilities of AI models. They are now collaborating with Physics Wallah to apply these advancements to the Alakh AI suite, improving its ability to solve complex problems and provide more reliable, step-by-step guidance to students. A key challenge is the nature of student queries, which are often ambiguous and involve multimodal inputs—text, images, videos, or audio—requiring unified capabilities to address the problem. Many STEM problems require breaking down complex queries into logical sub-problems and applying high-order, step-by-step reasoning for consistency. Additionally, integrating domain-specific knowledge in advanced math, physics, chemistry, and biology requires contextualization and seamless retrieval of specialized, grade-appropriate information.
Microsoft Research is working with Physics Wallah to move beyond traditional next-token prediction and develop AI systems that approach reliable, systematic, step-by-step problem-solving.
That includes ongoing work to enhance the model’s reasoning capabilities and deliver more accurate query answers on complex JEE math problems. Instead of just providing the final answer, the underlying models now break problems into step-by-step solutions. That helps students learn how to solve the actual problems. The AI can also review student answers, detect mistakes, and give detailed feedback, acting as a personal tutor to guide students, improve their understanding, and enhance their learning experience.
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Solving complex problems requires enhancing the reasoning capabilities of both large and small language models by training them to not just generate answers, but to systematically think through and reason about complex problems. This requires high-quality reasoning traces—detailed, step-by-step breakdowns of logical problem-solving processes.
To enable this, researchers collaborated with Physics Wallah to curate a dataset of 150,000 high-quality math reasoning traces. These traces serve as the foundation for training specialized small language models (SLMs) using supervised fine-tuning (SFT). Model performance is further refined through training on carefully curated on-policy preference data, ensuring alignment with high-quality reasoning standards. The team’s current Phi-based models have already outperformed leading LLMs and other baselines on complex math problems.
“Building AI systems capable of human-like thinking and reasoning represents a significant challenge.”
—Akshay Nambi, Principal Researcher at Microsoft Research India
The next step is to develop a self-evolving learning pipeline using online reinforcement learning techniques, allowing the model to continuously generate high-quality synthetic data that further enhances its capabilities. Additionally, researchers are building a reward model and integrating it with Monte Carlo Tree Search (MCTS) to optimize reasoning and improve inference-time decision-making.
“The goal is to develop tools that complement education. To do this, we are enhancing the model’s capabilities to process, break down, and solve problems step-by-step. We do this by incorporating high-quality data into training to teach the model how to approach such tasks, alongside algorithmic innovations that enable the model to think and reason more effectively.”
Listen or read along as Microsoft Research Podcast guest Akshay Nambi shares how his passion for tackling real-world challenges across various domains fuels his work in building reliable and robust AI systems.
Opening new doors for students
Getting an education at a top university can be life changing for anyone. For Chandramouleswar Parida, it could change the lives of everyone in his home village in Baniatangi, Khordha, Odisha State, India. Chandra decided to become a doctor after watching his grandfather die from a heart attack. The nearest doctor who could have treated him was at a regional hospital 65 kilometers away.
“He could have been saved if certain procedures had been followed,” Chandra said. He wants to study medicine, perhaps receiving advanced training overseas, and then return home. “I want to be a doctor here in our village and serve our people, because there is a lack of treatment. Being a doctor is a very noble kind of job in this society.”
Chandra is the only student in Baniatangi Village, Khordha, Odisha, currently preparing for the NEET. Without Physics Wallah, students like Chandra would likely have no access to the support and resources that can’t be found locally.
Another student, Anushka Sunil Dhanwade, is optimistic that Physics Wallah will help her dramatically improve her initial score on the NEET exam. While in 11th class, or grade, she joined an online NEET prep class with 800 students. But she struggled to follow the coursework, as the teachers tailored the content to the strongest students. After posting a low score on the NEET exam, her hopes of becoming a doctor were fading.
But after a serious stomach illness reminded her of the value of having a doctor in her family, she tried again, this time with Physics Wallah and AI Guru. After finishing 12th class, she began preparing for NEET and plans to take the exams again in May, confident that she will increase her score.
“AI Guru has made my learning so smooth and easy because it provides me answers related to my study and study-related doubt just within a click.”
—Anushka Sunil Dhanwade, Student
Next steps in the collaboration
The collaboration between Microsoft Research and Physics Wallah aims to apply the advancements in solving math problems across additional subjects, ultimately creating a unified education LLM with enhanced reasoning capabilities and improved accuracy to support student learning.
“We’re working on an education-specific LLM that will be fine-tuned using the extensive data we’ve gathered and enriched by Microsoft’s expertise in LLM training and algorithms. Our goal is to create a unified model that significantly improves accuracy and raises student satisfaction rates to 95% and beyond,” Govil explained.
The teams are also integrating a new tool from Microsoft Research called PromptWizard (opens in new tab), an automated framework for optimizing the instructions given to a model, into Physics Wallah’s offerings. New prompts can now be generated in minutes, eliminating months of manual work, while providing more accurate and aligned answers for students.
For Nambi and the Microsoft Research India team, the collaboration is the latest example of their deep commitment to cultivating the AI ecosystem in India and translating new technology from the lab into useful business applications.
“By leveraging advanced reasoning techniques and domain expertise, we are transforming how AI addresses challenges across multiple subjects. This represents a key step in building AI systems that act as holistic personal tutors, enhancing student understanding and creating a more engaging learning experience,” Nambi said.
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