Smartail, founded in 2019, is a global deep‑tech EdTech company transforming educational assessment through advanced AI and machine learning. Its flagship platform, DeepGrade, automates the grading of both handwritten and digital descriptive answers, delivering fast, unbiased scores alongside detailed analytics. These insights enable educators to identify learning gaps, personalize instruction, and make data‑driven decisions with confidence. By saving teachers time, enhancing evaluation quality, and generating actionable insights into student performance, Smartail’s AI-powered solutions are redefining classroom assessment.
Incubated by programs at HEC Paris and Station F, and recognized by IndiaAI and other international initiatives, Smartail now operates across India, the UK, the GCC, and beyond.
At the India AI Impact Expo 2026, Swaminathan Ganesan, Co-founder & CEO of Smartail, shared an exclusive conversation with The Interview World. He provided a detailed overview of Smartail’s AI-driven EdTech solutions, explained their applicability across different educational levels, highlighted the platform’s value to students, described the AI models powering the solutions, and emphasized the responses from schools and learners. Here are the key takeaways from his compelling discussion.
Q: Can you provide a detailed overview of the AI-driven EdTech solutions that Smartail offers, including their features, applications, and impact on learning outcomes?
A: We leverage AI to grade students’ answer papers and deliver comprehensive results and analytics to both teachers and students. By automating the grading process, we save teachers a significant amount of time, freeing them from the repetitive task of manual corrections. More importantly, our platform provides highly detailed, actionable insights at multiple levels: class, subject, chapter, topic, sub-topic, and even question type. This enables educators to pinpoint exactly where students are struggling and tailor remedial instruction accordingly. Instead of spending hours grading papers, teachers can now focus on addressing learning gaps, improving student understanding, and designing more effective lesson plans. Ultimately, our solution enhances evaluation quality, supports personalized learning, and empowers both teachers and students with real-time, data-driven insights into academic performance.
Q: Can you describe the full scope of solutions your organization provides and the different areas they cover?
A: We serve students across the entire educational spectrum, from K1 through K12 and into universities. Our platform supports first-grade learners as well as twelfth-grade students, adapting to each level’s unique curriculum and assessment needs. Beyond schools, we also collaborate with universities, extending our solutions to higher education. In this way, we provide a seamless, scalable approach that caters to learners at every stage, ensuring consistent, data-driven insights and personalized support from early childhood through advanced studies.
Q: What specific value or benefits do students gain from using your platform, in terms of learning outcomes, skills development, or overall experience?
A: Traditionally, when students received their answer papers, they saw only a set of marks and, if lucky, a few teacher comments. No detailed data accompanied their performance. We have transformed that process. For every answer paper, our platform shows students not just how they scored, but why they received, or lost, specific marks. This adds real value to the feedback. Instead of a paper marked in red ink with little explanation, students now understand exactly where they fell short and how to improve. For instance, if a five-mark question earns only two marks, we explain why the remaining three were lost and what steps they can take to earn full credit. All of this is accessible through our mobile app, giving students a detailed, actionable analysis of their results.
Q: Can you explain which AI models your platform leverages?
A: We operate a multi-model architecture, developing specialized AI models for distinct purposes. For instance, one model identifies a student’s roll number, while another evaluates the quality of the content in an answer. Each model is purpose-built and continuously refined through repeated training to ensure accuracy and reliability. Unlike general-purpose LLM systems, our approach relies on multiple targeted models, each optimized for a specific task. This design allows us to achieve precise, context-aware results across different aspects of assessment, ensuring that every function, from identification to content evaluation, is handled with maximum efficiency and effectiveness.
Q: Has your organization established any collaborations with educational boards in India?
A: No, we are still a relatively small company. Our boards require at least 1,000 schools to adopt our platform before we engage in formal discussions with education boards. That said, we have already initiated early conversations with several boards and continue to explore opportunities as we expand our reach.
Q: What responses have you received from schools and students regarding your platform?
A: Three years ago, responses to our platform were lukewarm. Today, however, the AI wave has sparked tremendous interest. When we approach ten schools, at least eight are eager to hear us out, and seven typically agree to run a pilot to evaluate our solution firsthand. This shift highlights the growing recognition of AI’s potential to transform educational assessment and underscores the increasing receptivity of schools to innovative, data-driven tools.
