Shahzad Ahmed

Shahzad Ahmed is a co-founder of Hoja AI, a London edtech startup using adaptive AI to personalise study and exam preparation for GCSE students across the UK.
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Shahzad Ahmed is a British-Pakistani entrepreneur and co-founder of Hoja AI, the London-based education technology startup building a personalised AI study application for school-age learners. Ahmed co-founded the company in 2024 alongside CEO Pavan Konanur and Katherine Tatarinov, with a shared mission to make high-quality, genuinely personalised education accessible to every student — not just those whose families can afford individual tutoring.

Ahmed’s background spans software engineering and AI product development, with particular expertise in the technical architecture required to build adaptive learning systems that respond meaningfully to individual users rather than following static content paths. The challenge of building a platform that can genuinely model a student’s knowledge state — understanding not just what they have studied, but what they have retained, where their conceptual gaps lie, and what type of explanation they respond to best — is a demanding engineering and AI problem, and Ahmed’s technical foundation was central to Hoja’s early product development.

Hoja’s platform is built around multimodal AI: combining chat-based tutoring, adaptive quizzes, and personalised content generation into a system that continuously recalibrates to each learner. The company is focused on GCSE students and operates on a freemium model, with monetisation through premium features including advanced exam preparation tools and deeper personalisation. Students are reached primarily through digital marketing and community engagement, reflecting a direct-to-learner strategy rather than a school-led procurement model.

The company raised £1.3 million in 2024 to develop its AI capabilities, expand subject content coverage, and grow its user base. Ahmed’s co-founding role at Hoja places him at the intersection of two of the most significant technology trends of the decade: the rapid maturation of large language models and the long-overdue transformation of how young people study and prepare for high-stakes exams.

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