1. How long have the founders known one another and how did you meet? Have any of the founders not met in person? We have known each other since 2015. We met during our undergraduate degree in Georgia Tech and were also roommates. 2. Who writes code, or does other technical work on your product? Was any of it done by a non-founder? Please explain. The code and technical work for the product is done by both of the co-founders. Vignesh handles the web application while Likhit is responsible for the AI models. 3. Please record a one minute video introducing the founder(s) https://drive.google.com/file/d/16Nc_EVeUs45-ClvlENHJZ4CZQ5LEutBl/view 4. Company name Ira Project 5. Describe what your company does in 50 characters or less We help students learn by teaching an AI study buddy 6. Company url https://github.com/Ira-Project 7. If you have a demo, attach it below https://drive.google.com/file/d/1z1Ii3Tw_d_QTFEKX9IypjnnW1VLvIFtg/view 8. Please provide a link to the product, if relevant. bushwhack-one.vercel.app/ 9. What is your company going to make? Please describe your product and what it does or will do? We are building an AI study buddy that students can teach concepts to. Instead of answering questions, students have to explain to our AI how to solve them. Using the knowledge from the explanation given by the student, our AI attempts to solve a set of questions. The students iterate on their explanation till our AI is able to solve all the questions correctly. 10. Where do you live now, and where would the company be based after YC? Bangalore, India / San Francisco, USA 11. Explain your decision regarding location. The founders are currently based out of different locations. Vignesh lives in Bangalore, India while Likhit is completing his PhD at Georgia Tech. We are hoping to build this product in San Francisco so we can be close to the cutting edge in AI. 12. How far along are you? We have built out a basic MVP and begun user testing. We have so far tested it with five of our students. While using the product, the students had to exercise metacognition and it revealed quite clearly gaps in their understanding. We have also interviewed five teachers and have got a buy in from three of them to use it in their classrooms next year. 13. How long have each of you been working on this? How much of that has been full-time? Please explain. Vignesh has been working on the product full time for the last four weeks. Likhit has been working part time while wrapping up the final stages of his PhD (graduating in Summer). 14. What tech stack are you using, or planning to use, to build this product? We're using NextJS deployed on Vercel for our web application. Currently, the AI works through prompt engineering using GPT-4 assistants. We have started creating a dataset to fine tune an open-source LLM. 15. Are people using your product? When will you have a version people can use? No. We haven't publicly launched yet, we are still iterating over our initial MVP with user testing. We are planning to release a classroom ready version for customers in a month. 16. If you are applying with the same idea as a previous batch, did anything change? If you applied with a different idea, why did you pivot and what did you learn from the last idea? (Vignesh has applied to YC with a different idea while this is Likhit's first application.) For the first time I'm applying with a product where I experience the problem myself. Solving a pain point I've experienced firsthand made the development process a lot easier and has given me the conviction needed. There were a few things I learnt from previous ideas: - It's important to perform high quality reps. In OpenOS we often pivoted and iterated without learning as much as we should have. - Finding the sweet spot for an MVP. It's about finding the balance between creating a functional product while remaining flexible enough to adapt to customer needs quickly. - Acquiring early customers requires doing lot of things that don't scale. There was almost a service like element with our first few customers at OpenOS. 17. If you have already participated or committed to participate in an incubator, "accelerator" or "pre-accelerator" program, please tell us about it. Vignesh participated in Pioneer in his previous startup. Pioneer was a great experience and spending three months in SF surrounded by founders lead to rapid learning. It also made the journey a lot less lonely and it was often very helpful to run ideas by and brainstorm with fellow founders. 18. Why did you pick this idea to work on? Do you have domain expertise in this area? How do you know people need what you're making? The Ira Project was born out of our own needs while working in education. Vignesh runs a non profit which creates after-school learning spaces for marginalised children. Likhit has taught multiple courses at different universities and is involved in administration of his school in Bhubaneswar, India. While working with students, both of us struggled with gauging how well a student understood something. The traditional tests and assignments didn't identify the gaps in conceptual understanding. Often we would have to give personalised attention and we found that asking a learner to explain a concept back to us was revealing. 19. Who are your competitors? What do you understand about your business that they don't? FlintK12, Khan Academy, Kahoot There are three areas where we differ from the competition and where we feel our understanding is different 1. Learning through creation not consumption. Most of the products today have students consuming content. When students teach an AI model we're allowing them to create something thus providing a different learning experience. 2. Known Unknowns vs Unknown Knowns. Products today largely focus on helping users learn something they don't know about. Instead, our product relies on metacognition and helps students discover what they know and how they know something. 3. Workflow. Though we have only interviewed a few teachers, they all feel like the AI EdTech products are out to replace them. Many are creating AI teachers or AI tutors and there is an inherent fear. Our product fits seamlessly in the teacher's workflow (even the questions and assignments they create need not change) and aims to enable them. 20. How do or will you make money? How much could you make? Currently we're thinking of a freemium model. Our current thought process is to provide a free tier for students to use so we can acquire more data. For schools, we plan to charge them to administer and access tests/assignments for their students. 21. How do users find your product? How did you get the users you have now? If you run paid ads, what is your cost of acquisition? Our first users for this product are going to be students in Vignesh's non profit and Likhit's school. The next few users will be from our personal network. We have worked with schools in Atlanta and have close friends who are teachers. 22. Where will most of your initial users be located? United States 23. If you have not formed the company yet, describe the planned equity ownership breakdown among the founders, employees and any other proposed stockholders. If there are multiple founders, be sure to give the proposed equity ownership of each founder and founder title (e.g. CEO). (This question is as much for you as us.) Vignesh Prasad, Chief Executive Officer - 50% Likhit Nayak, Chief Technology Officer - 50% 24. If you had any other ideas you considered applying with, please list them. One may be something we've been waiting for. Often when we fund people it's to do something they list here and not in the main application. Blood pressure measurements can be key indicators for a variety of medical conditions. The point-of-care tools for these measurements work only on superficial sites like the wrist or the thigh. By using PINNs (physics-informed neural networks), we can develop models that use the measurements from a set of superficial sites and predict pressure and flow at interior locations like the heart or the uterine artery. These models can then serve as early risk indicators for different conditions like preeclampsia. 25. What convinced you to apply to Y Combinator? Did someone encourage you to apply? Have you been to any YC events? Over the years we've met many YC founders, have watched lots of YC content, and attended a few events. We've heard about the value it can provide. When we saw the recent light cone podcast on how AI companies were built at YC it only reaffirmed our idea on how YC could give us the competitive advantage necessary to build a large company. 26. How did you hear about Y Combinator? We heard about YC from our friends back in college.