What if education could reach every child the way money reaches every wallet? That was the central provocation Jairaj Bhattacharya, Co-founder of ConveGenius, brought to the India AI Impact Summit 2026 in New Delhi.

Joining global leaders from the Gates Foundation, Fab AI, and IDinsight, Jairaj took part in a high-stakes panel: "Building High-Quality AI Systems for Education: From Innovation to System-Wide Impact" , tackling one of EdTech's most stubborn challenges: moving beyond isolated pilots to AI ecosystems that shift learning outcomes at a national scale.


L-R: Kalpana Sharma(Lakshmibai National Institute of Physical Education), Jonathan Stern(Gates Foundation), Marc Shotland(IDinsight), Romana Kropilova(Fab AI), Jairaj Bhattacharya(ConveGenius)



“If fintech could reach the last mile, so could education. The idea here was ‘how do we get AI to the last mile’ , like how UPI has done it in fintech. How do we do that for education?”.

Mr. Jairaj Bhattacharya
MD & CoFounder at ConveGenius.AI

But taking conversational learning to a national scale requires more than intelligent models. It requires infrastructure built for massive demand. Standard messaging APIs typically cap at roughly 30,000–40,000 requests per minute. SwiftChat’s native protocol, by contrast, is engineered to handle 150,000–200,000 requests per minute, making it capable of supporting deployments that reach hundreds of millions of learners.

The behavioural advantage of messaging also matters. People instinctively respond to messages on their phones. As a result, conversational learning systems see response rates as high as 99%, making AI tutoring both highly engaging and available 24×7.

At the same time, scale without trust is not sustainable. A DPDP Act–compliant architecture ensures that governments can host student data securely within their own infrastructure, enabling both scale and data sovereignty for public education systems.

Yet infrastructure alone does not solve the learning problem. For ConveGenius, scale without learning impact is merely reach. Jairaj described the company’s approach as “pedagogical engineering”, designing systems that know precisely what to show a child, and when, to maximise retention and learning outcomes.


PAL accelerated learning gains for students

This focus on learning impact has also been tested externally. Marc Shotland of IDinsight referenced an independent evaluation led by Nobel Laureate Michael Kremer, which found that students using ConveGenius’ platform achieved more than double the learning gains over 17 months compared to a control group.

But the larger insight extends beyond any single technology or company. AI alone will not transform education. Systems will. The real opportunity lies in building infrastructure that allows high-quality AI to reach the last mile of learning, much like UPI enabled financial services to reach millions of people across India. The future of education will depend not only on innovation but on the systems that allow that innovation to reach every classroom, every teacher, and every child.

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