How A Tactical Shift Took Masai School To The INR 100 Cr Revenue Club

Bengaluru-based upskilling startup Masai School learned a lesson the hard way. 

Its pay-after-placement model began scorching its coffers when the startup ecosystem went into a two-year funding winter that drew a freeze on hiring and slammed the brakes on expansion. The edtech startup saw its revenue decline 11.43% from INR 36.84 Cr in FY23 to INR 33.06 Cr in FY24. 

It wasn’t steep, but it blew the lid off a reality that the company could not preempt since it set sail in 2019. 

Founder trio Prateek Shukla, Nrupul Dev and Yogesh Bhat designed Masai School to offer full-stack development and data analytics courses based on the ‘pay after placement’ model and ran the show on income sharing agreements (ISAs). 

Students signed up for training with no upfront fees and paid through fixed monthly instalments over 36 months only after getting placed.

“This approach helped us attract students that eventually translated into revenue, but left little room for us to manage cash cycles,” Shukla said while sharing with Inc42 how the company paused and hit the reset.

In fact, the business ran into negative working capital with the expenses mounting and the bottomline looming. Its losses hit INR 42.04 Cr in FY24, when layoffs turned rampant in the startup economy. 

It was time to take some tough decisions. Between FY22 and FY25, the founders began restructuring the company’s internal systems and operating approach. Revenue was just one part of the problem. The model itself had to shift.

Masai introduced a prepaid option, brought in AI-backed courses, reined in expenses, and recalibrated the curriculum and placement design. All these paid off as Masai shrank its losses by 69% to INR 13.2 Cr in FY25 from INR 42.04 Cr a year back and widened its revenue close to INR 100 Cr.

Shukla also claimed that the company turned EBITDA positive in January 2025, though Masai is yet to share its audited financials for FY25. 

Deconstructing The Harder Problems 

Masai School had its pay-after-placement (ISA) model built around the assumption that all learners would seek full-time employment on completion of their courses. But, in reality, not every student at Masai was aiming for the same outcome. 

Some joined the programme to upskill for freelancing or building their own products. Others, particularly from smaller towns, were not open to relocating for jobs, which had a direct impact on placement rates. This meant that even if a student completed the course, Masai didn’t always recover the training cost.

The outcome of the income-sharing model was, however, strong for those who aimed for placements. Masai had placed more than 7,000 learners across companies with an average package of INR 6.1 LPA, driving the placement rate to 94% by 2023. There was another rider, though. The mechanism only worked when jobs were secured and sustained – something that couldn’t always be guaranteed.

The programme structure added another layer of limitation. The flagship curriculum followed a full-time, 11AM-to-11PM schedule for six days a week. It included 1,200 hours of coding, 100 hours of soft skill training, and 100 hours of mathematics. While effective, this structure left no flexibility for working professionals – a segment that could be keen on upskilling, but couldn’t commit that kind of time.

“What IITs and NITs teach their students in four years, we had to sum it up in six-seven months. By design, they had to be full-time and rigorous,” Shukla argued.

Then came the external shock. The Covid pandemic in 2020 had shaken the world, but shuddered the digital economy to run into the fast lane. Masai was a beneficiary of a hiring overdrive by startups. Placements surged, and in sync, soared operational losses. 

The ebbing of the Covid waves set off ripples of a recessionary wave around the world, which was further accentuated by Russia’s war on Ukraine. Blazing inflation and soaring interest rates made venture capitalists shy of making fresh commitments.

“With the hiring freeze across the startup ecosystem, nearly 80% of our core business of placing trained candidates into startups like Swiggy, Meesho, Ola, ClearTrip and Paytm flatlined,” said Shukla.

Between 2022 and 2024, Inc42 data shows that 37,264 people were laid off across 130 Indian startups. At least 264,220 were fired by 1,193 tech companies in 2023 alone and 152,922 were sacked by 551 tech firms the next year. 

For Masai, which was grappling with internal problems, the market collapse served a compounding blow, halting revenue momentum and forcing a hard pivot.

Cracking The Puzzle, Piece By Piece 

To regain stability and steer towards sustainability, Masai School brought in a series of structural changes in its business model – spanning across curriculum delivery and market positioning. 

Recasting The Pay-After-Placement Format

According to Masai’s initial model, students who secured jobs had to pay a fee of INR 3.5 Lakh, regardless of the salary they earned. This format increasingly misaligned with market conditions, especially as the average pay began to drop and hiring slowed down.

To address this, Masai introduced a tiered pricing model. Under this structure, students placed in jobs with salaries of INR 3.5 Lakh to INR 4.99 Lakh a year would pay INR 2.5 Lakh to the startup. Those placed in the INR 5-9.99 LPA range would continue with the earlier INR 3.5 Lakh fee. Students earning INR 10 LPA or above would pay INR 4.5 lakh. 

All payments are broken into EMIs. This ensures that repayment expectations are proportional to a student’s outcome and preserves the viability of Masai’s placement-linked revenue model, even as average CTCs declined.

With the tiered model in place, Masai retained its placement rate and aligned repayments to the actual earnings of graduates.

Masai raised $14.7 Mn in two successive funding rounds – $4.7 Mn in a Pre-Series B round and $10 Mn in its Series B round in 2022 – to create room for expansion of business, recalibration of offerings, and investment in new formats.

Building Prepaid Programme With Prepleaf

To de-risk its revenue from hiring cycles, Masai devised a prepaid course and introduced it through Prepleaf, which it had acquired in 2021. In October 2023, Masai launched the course under Prepleaf’s Scholar Program, allowing students to pay upfront and gain access to relevant training modules without depending on placement outcomes.

The prepaid courses were launched in collaboration with a host of IITs and IIMs. These partnerships led to the co-creation of six-to-nine-month programmes that focussed on both employability and long-term skill development.

The programmes were designed for three categories of learners. First, working professionals seeking to upskill. Second, college students looking to gather industry skills. And, third, learners from lower-income backgrounds or small towns who could not afford high-cost professional education.

Masai ensured that courses were affordable, starting at INR 60,000, which was significantly lower than INR 5 Lakh, which is typically charged for executive education at premier institutions. More than 20,000 students enrolled in these prepaid courses, with the majority coming from Tier III and IV towns and rural areas.

The prepaid courses helped Masai jack up its topline by 106% from INR 17.85 Cr in FY22 to INR 36.84 Cr in FY23.

Realigning With Original Principles By Misogi AI

Masai introduced Misogi AI in mid-2023 as a full-time, 14-week advanced artificial intelligence programme to meet the demand for AI-readiness among working software developers. It allowed Masai to reintroduce a no-cost education path for learners, without depending on upfront student payments or post-placement income shares.

Misogi AI required the learners to commit 90–100 hours a week. Many participants took sabbaticals from their jobs to complete the course. Employers too often bore the cost of the training, and in return, received employees equipped to implement AI in their existing product and engineering systems.

“This model reflects a broader shift in how AI is changing the way we learn. The industry has moved from MOOCs to cohort-based education, and now personalisation has become a mandate. Today, AI has enabled personalisation at scale and Masai School has doubled down on that front,”  Shukla said.

Expanding Into AI-Powered Job Matching

As part of building its own tech-led recruitment infrastructure, Masai launched Placed, an AI-powered talent platform, designed to connect job seekers to relevant roles based on skill-based vetting.

Unlike traditional job platforms, Placed focussed on expanding access to talent from smaller towns – who stayed under the formal hiring radars of tech employers. The platform was opened to candidates beyond the Masai ecosystem. Once vetted by the AI engine, candidates could be matched with suitable job openings.

The platform positioned itself against incumbents like Naukri and LinkedIn. “We launched Placed around one-and-a-half months back and we already got 170,000 job seekers on the platform,” Shukla claimed.

Survival Secured, Can It Scale?

Masai School built itself around a simple idea: education must lead to employment. The focus on outcomes has been key to its brand identity, particularly in Tier III towns. For many students, Masai came to represent a place where industry-aligned learning translated into a real shot at a career.

“Masai has worked with around 25,000 students so far and helped lift over 1,000 families out of poverty,” Shukla claimed.

That brand pull has paved the way for scaling. “We see stronger performance metrics than many of our peers, even those valued at $100–500 Mn, because we stayed focussed on outcomes over noise – training students for high-quality jobs and charging only when those jobs are secured.”

Masai is now aiming for a full-year run rate of INR 195–220 Cr in FY26. In fact, the company hopes to reach profitability this year with a net of around INR 35 Cr.

There are, however, challenges along the way. While its revenue regained, its expenses surged from INR 75.11 Cr in FY24 to a projected INR 112.63 Cr in FY25, largely because of higher marketing spends and revenue-sharing commitments with IITs and IIMs. It also included investments in Masai’s Faculty Development Program, which is designed to upskill college faculties.

Shukla said AI-led processes have also helped it control employee costs, even as topline numbers climbed and, in turn, secure operational efficiency.

Masai has also started looking beyond India. Through its Misogi AI programme, it is testing opportunities with international recruiters engaging with its first graduating cohort.

In many ways, Masai’s model remains unchanged in principle: train learners rigorously, link them to employment, and remove any excess friction in between. But the way forward will demand more than recovery. As more players enter the space and the demand for outcome-linked learning grows, Masai School will need to defend the very edge that brought it this far. 

Edited by Kumar Chatterjee