
Cerebry
At Cerebry, our aim is to make effective personalised tuition accessible to each and everyone, regardless of geography or family income.
Date | Investors | Amount | Round |
---|---|---|---|
investor | €0.0 | round | |
investor | €0.0 | round | |
investor | €0.0 | round | |
* | $1.0m Valuation: $13.3m 0.5x EV/Revenue | Seed | |
Total Funding | 000k |
USD | 2022 | 2023 |
---|---|---|
Revenues | 0000 | 0000 |
EBITDA | 0000 | 0000 |
Profit | 0000 | 0000 |
EV | 0000 | 0000 |
EV / revenue | 00.0x | 00.0x |
EV / EBITDA | 00.0x | 00.0x |
R&D budget | 0000 | 0000 |
Source: Dealroom estimates
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Cerebry, established in 2015, is an education technology firm focused on democratizing personalized tutoring through artificial intelligence. The company was co-founded by Rahul Singhal, Shubham Goyal, and Rohit Kapur, all of whom are alumni of the National University of Singapore. Their collective experience in data science and engineering underpins the company's technological foundation.
The firm operates within the global EdTech market, targeting educational institutions such as schools and publishers rather than individual students directly. This business-to-business-to-consumer (B2B2C) model involves integrating its AI-powered practice tool into the existing curricula of its clients. Revenue is generated by licensing this technology to these educational partners, who then provide it to their student populations. This approach allows Cerebry to scale its reach significantly by leveraging the established networks of schools and publishers.
Cerebry's core offering is an AI tutor that creates customized practice problems for students, primarily in STEM subjects. A key differentiator is its ability to generate questions in real-time that are tailored to a student's specific skill level, moving beyond the limitations of a static, predefined question bank. The AI analyzes a student's performance on a given problem and can dynamically adjust the difficulty of subsequent questions, offer step-by-step guidance, or even introduce foundational concepts if it detects a knowledge gap in a prerequisite topic. This adaptive learning system aims to replicate the experience of working with a one-on-one human tutor, providing a personalized learning path for each user.
Keywords: AI tutor, EdTech, personalized learning, adaptive learning, STEM education, B2B2C, question generation, practice tool, educational software, student assessment