Most education funding rounds are bets on software. Mesa School of Business is a bet on the campus itself.
The Bengaluru institution has raised ₹110 crore, comprising roughly ₹85 crore in Series A equity co-led by Dharana Capital and existing investor Elevation Capital, plus ₹25 crore in venture debt from InnoVen Capital and Alteria Capital. Mesa says the money will strengthen its leadership team, expand AI-led program design, launch new offerings and deepen partnerships with startups.
The round values Mesa at roughly ₹385 crore post-money. Mesa previously raised ₹34 crore in 2023, when Elevation Capital backed a founding postgraduate cohort of just 60 students.
Mesa was founded by Ankit Agarwal and Varun Limaye, whose backgrounds help explain its operator-first model. Agarwal’s experience spans IIT Bombay, BCG, Urban Company and Harvard Business School, while Limaye’s background includes Kellogg, Pratham and Amazon. Mesa’s own positioning reflects that mix of startup operating experience and business education, with both founders emphasizing learning through building rather than classroom theory alone.
Three years later, Mesa says it has 550+ students across three core programs: its 12-month PGP in Startup Leadership & Entrepreneurship, the Forge venture-building program for recent graduates, and a four-year undergraduate program.
That growth matters because Mesa is not trying to reproduce the traditional MBA model.
Its flagship PGP is explicitly a Mesa-issued certificate of completion, not an MBA, PGDM or university degree. Its four-year undergraduate program is also a non-degree certificate program; students who want a formal bachelor’s qualification can separately enroll in an online degree from a university such as NMIMS or IIM Bangalore, subject to that university’s own requirements.
In other words, Mesa is asking students to value what they build and do as much as the credential itself.
That philosophy runs through the curriculum. Mesa’s UG program currently lists 600+ hours of applied business learning, 150 hours of AI learning, 75+ case studies and exposure to 25+ AI tools. Students work with products such as ChatGPT, Claude, Codex, Lovable, Replit and automation platforms while studying finance, marketing, product, operations and venture building.
Its postgraduate AI curriculum goes further into applied workflows, including AI product architecture, voice-agent building, AI go-to-market and selling AI products. The distinction is important: AI is being positioned as an operating skill inside business education rather than as a standalone technology elective.
Mesa also makes students test that learning outside a classroom. In its first undergraduate cohort, 24 teams generated ₹75 lakh in collective revenue during an eight-week Build Your Own Business program. Mesa is careful to describe that number as business revenue, not profit or individual student earnings.
The school’s in-house Mesa Startup Lab adds another layer. It provides access to a ₹5 crore startup fund, while Mesa says it has invested more than ₹1.2 crore directly into student ventures to date.
For its more established PGP, there is now a measurable employment record. Mesa’s published outcomes methodology reports an average CTC of ₹26 lakh across 127 graduates in full-time roles from its first two cohorts, with compensation methodology disclosed separately.
The undergraduate program is earlier in its proof cycle. Its founding cohort began in 2025 and is expected to graduate in 2029, so Mesa does not yet have graduate placement outcomes for that program.
That makes the new financing particularly significant. Dharana and Elevation are not simply financing a larger version of Mesa’s original PGP. They are backing whether this high-touch, startup-connected, AI-heavy education model can scale across different stages of a student’s career without weakening the outcomes that made the first program compelling.
The next test is therefore not enrollment growth alone.
It is whether Mesa can expand from hundreds to potentially thousands of students while preserving the things its model depends on most: real projects, founder access, credible outcomes and enough hands-on building that “AI-first” remains an operating capability rather than a curriculum label.
