Artificial intelligence is already finding its way into classrooms, but the bigger challenge for schools may not be access to AI itself. Teachers and students can already choose from a growing number of AI tools for lesson planning, research, assessments, content creation and learning. The harder question is how these tools fit into the larger education system without creating another layer of disconnected technology.
That is the problem Chiranjeevi Maddala, Co-founder and CEO of AI Ready School, believes the company is trying to address. With more than 25 years of experience spanning design, technology and education, Maddala argues that schools need to move beyond experimenting with individual AI applications and towards a more structured approach that connects students, teachers, learning, skills and school infrastructure.
AI Ready School, or AIRS, describes its platform as an integrated AI ecosystem for K-12 education. Its approach brings together student learning, teacher assistance, AI tools, innovation labs and infrastructure rather than treating each use case as a separate product. The company says it has worked with more than 20,000 students and 500 teachers across 30-plus schools, including private and government schools, as well as institutions in the US and Uzbekistan.
The company’s approach also comes with a stated philosophy: “Human First, AI Next.” For Maddala, that means using AI to support teachers and students rather than allowing technology to replace human judgment or turn learning into a process of simply obtaining answers.
AIRS is also attempting to build evidence around its approach. Its “100 Schools, 100 Pilots” initiative is intended to contribute to a national research programme examining how AI affects teaching and learning across different types of Indian K-12 schools. The company says it plans to measure learning gains, reasoning confidence, teacher feedback and student engagement across government and private schools, different geographies and multiple curricula.
In this interview with techinfoBiT, Maddala discusses the thinking behind AI Ready School, how its products are intended to work together, the challenges of deploying AI in government schools, the company’s market opportunity and its plans to reach 500 schools by 2027. He also explains why the platform’s product names draw directly from The Matrix films.
Interview with Chiranjeevi Maddala, Co-founder & CEO, AI Ready School
1. What gap in K-12 education led you to build AI Ready School, and why did you believe existing AI tools were not enough?
The challenge was never a lack of AI tools. It was the absence of a system to use them effectively. Over my 25 years of experience across design, technology and education, including building Digital Ready in 2011 and later working at igebra.ai, I watched schools experiment with ChatGPT, Gemini, Perplexity and a dozen point solutions, each solving a narrow problem in isolation. A teacher would use one tool for lesson plans, another for assessments, a third for student doubts, none of them talking to each other, none of them building a cumulative understanding of the student.
That’s the core insight behind AI Ready School, where using individual AI apps is seen not as AI adoption but as AI fragmentation. A school doesn’t need another answering machine. It needs an operating system, one that understands every student across knowledge, learning style, cognitive behaviour and skills, and delivers “the right instruction to the right student at the right time.” Existing tools could automate a task. None of them could hold that 360-degree picture of a learner over time, which is what true personalisation actually requires. That’s the gap we built the platform to close.
2. AIRS has five products: Mars, Morpheus, Zion, NEO and Matrix. How do they work together within a school?
Think of them as five layers of the same operating system, each serving a different person in the school. Mars is the student’s personal AI learning companion, which is always available, multimodal, and built to make students think rather than just hand them answers. Morpheus sits on the teacher’s side, turning lesson planning, content creation and assessment into an agentic workflow that can cut content-creation time by up to 75%, while giving teachers a 360-degree view of every student’s knowledge, learning style, cognitive behaviour and skills.
Zion is the connective tissue, a suite of 30+ AI tools across learning, creative, research and project use cases that both Mars and Morpheus can call on directly. NEO is the AI Centre of Excellence, which is the physical and digital lab where students take what they’ve learned and turn it into real projects, research papers, and competition entries, with a built-in LMS and workspace. Matrix is the infrastructure layer underneath everything, with on-campus AI servers and models that ensure a school’s data never has to leave its own premises, along with surveillance, classroom monitoring and reception systems that run on the same local infrastructure.
Together, a lesson a teacher builds in Morpheus can pull tools from Zion, feed a student’s progress data into Mars, surface project opportunities in NEO, and run for schools that choose it, entirely on their own Matrix infrastructure. It’s one continuous loop, not five separate products.
3. You use the philosophy “Human First, AI Next.” How does that philosophy translate into the actual product experience for students and teachers?
It is reflected in the design itself rather than presented merely as a slogan. For teachers, “Human First” means the platform gives them flexibility and control rather than a fixed set of content. They define their own methods and best practices, and Morpheus follows those instructions rather than replacing their judgment. AI speeds up the mechanical parts of teaching, whether it is lesson creation, test generation, or evaluation, specifically so teachers get time back for the parts only a human can do, such as building relationships with students and focusing on the creative aspects of teaching.
For students, it means Mars is deliberately not built to be an answering machine. It’s designed to ask questions back, to make students think, because we believe the question matters more than the answer when someone is actually learning. Every interaction has child-safety guardrails and full parental visibility built in. So “Human First, AI Next” is not about using less AI. It is about sequencing it correctly, with AI supporting human growth and judgment rather than replacing either.
4. How does Morpheus help teachers in their day-to-day work, and what impact have you seen on teacher workload or productivity?
Morpheus takes teachers through a structured workflow that begins with configuring a lesson using their own source documents, textbooks or PDFs, followed by an AI-generated outline they can review and edit, multimodal content such as presentations, 3D visualisations and questions, a theatre-mode preview showing exactly how students will experience the lesson, and finally, assignment and progress monitoring from a single platform. That collapses what used to be hours of separate prompting, formatting and searching into a single guided process. We’ve seen up to 75% time saved on content creation, test creation and evaluation.
Beyond the time saved, the bigger shift is in insight, not just output. Teachers get a 360-degree view of every student across knowledge, learning style, cognitive behaviour and skills, something that was simply not possible to track manually across a full classroom. That is what lets a teacher move from teaching the syllabus to actually closing individual learning gaps in real time.
5. AIRS says it has reached 20,000+ students and 500+ teachers across 30+ schools. What measurable outcomes or learnings have you seen so far?
The clearest data point so far comes from a case study conducted with B.P. Pujari Government School in Raipur in February 2026, which examined AI-enabled peer learning in middle school mathematics. Against a baseline assessment, we saw a 34% increase in final class scores, a 57% improvement in application-level cognitive tasks, and a 77% improvement in analysis-level cognitive tasks. That last number matters most to us; it tells us the platform isn’t just helping students recall content faster- it’s improving how they reason through it.
Across the 20,000+ students, 500+ teachers and 2,000+ platform users we’ve worked with so far, the broader learning has been about adoption patterns: usage is highest and stickiest when teachers are given control rather than a fixed curriculum, and when students experience AI as something that makes them think rather than something that gives them shortcuts. Both of those learnings have directly shaped how we’ve built the product.
6. Your “100 Schools, 100 Pilots” initiative aims to support a national research programme. What exactly are you measuring through these pilots?
That initiative is what sits behind AIRS Research’s national study, “How AI Impacts Teaching and Learning in Indian K-12 Schools.” Each participating school commits one grade, one section and one subject to a short on-campus session, and we measure genuine shifts in understanding using pre- and post-session assessments on equivalent, non-repeating test forms, so we’re capturing real learning gains, not just familiarity with a repeated test.
Alongside that, we run a reasoning-confidence measure, because how confident a student feels in their own thinking is a dimension test scores alone don’t capture. We also collect structured feedback from teachers on how the session changed their lesson delivery, pacing and assessment, and structured feedback from students on engagement and confidence. We’re deliberately drawing that 100-school sample across government and private schools, urban and rural geographies, and CBSE, ICSE, State board and international curricula, so the findings represent Indian K-12 education broadly rather than one type of school. The compiled findings will become a national research report, launching in Delhi on January 28, 2027, guided by an independent research advisory panel that includes Janajit Ray.
7. How does AIRS address concerns around student privacy, data security, AI-generated misinformation and responsible use of AI in schools?
Privacy and safety are built into the infrastructure layer, not bolted on afterwards. Matrix gives schools sovereign, on-campus AI infrastructure through local servers and models, ensuring that sensitive student and staff data remains on the school’s premises without third-party exposure or reliance on the cloud for core operations. Zion, our AI tool suite, has age-appropriate filters and teacher-managed access for every tool a student can use.
On the research side, individual student results from our AIRS studies are kept confidential and anonymised in any published report; a school is only named with its explicit consent, and all data handling follows applicable Indian data-protection requirements for information relating to minors. On misinformation specifically, this is why Mars is designed to make students question and reason rather than simply accept an AI-generated answer at face value, because responsible use begins with teaching students how to critically engage with AI output rather than relying solely on a policy document.
8. AIRS has worked with private schools, government schools and institutions in international markets. How different are their needs when it comes to AI adoption?
The needs may differ in scale and context, but the underlying challenge remains the same across private, government and international schools, which is how to personalise instruction for every student without significantly increasing the teacher’s workload. Private schools, which our data shows already have roughly half their students using generative AI multiple times a week, often informally, tend to come to us wanting structure and safety around usage that’s already happening.
Government schools are usually starting from a more blank slate, which in some ways makes structured adoption easier since there is no informal, ungoverned usage to unwind first, as our Raipur case study is a good example of what is possible in such settings.
International markets, where we have a footprint across the US and Uzbekistan alongside India, bring different curriculum and regulatory contexts, but the core product philosophy, i.e., teacher control, student-first personalisation, on-campus data sovereignty, travels well because it isn’t tied to any one board or country’s syllabus. What changes market to market is largely the configuration, not the underlying system.
9. You also work with government schools. Given that many government schools still face basic infrastructure challenges, how realistic is large-scale adoption of AI-based platforms in this segment?
It’s realistic, but only if you design for it rather than assume it away. Our Raipur pilot with B.P. Pujari Government School is proof that meaningful outcomes- a 34% score increase, a 77% improvement in analysis-level tasks are achievable in a government-school setting. But we didn’t get there by expecting government schools to have the same connectivity or device access as a well-funded private school.
This is precisely why Matrix exists as a separate, non-subscription infrastructure layer, providing a local AI server that can run on campus with reduced dependence on constant internet connectivity for core AI tasks. It is also why the AIRS Research study is deliberately structured as a small, well-defined commitment involving one grade, one section and one subject over a short on-campus session, rather than a full rollout. This approach means participation does not require a government school to address every infrastructure gap before it can begin. Large-scale adoption in this segment is realistic when the model is phased, infrastructure-light where necessary and able to demonstrate value through a contained pilot before requiring broader investment.
10. Who is your primary target customer today, and how large do you see the market opportunity for AI Ready School in India?
Today, our primary customer is the K-12 school itself, with school leadership making an institutional decision to adopt AI as a system rather than an individual teacher or parent buying a standalone tool. At the same time, the products are designed to serve teachers, students, parents and school management within that ecosystem. We are seeing traction across a genuine mix of schools, including international and CBSE and ICSE private schools as well as government schools, suggesting that the need for structured AI adoption extends across different segments of the market.
The opportunity is equally broad. India’s K-12 education sector is estimated at around $76.8 billion and is projected to cross $144 billion by 2030. At the same time, the Ministry of Education has announced that Artificial Intelligence and Computational Thinking will be introduced from Grade 3 onwards from the 2026–27 academic session, aligned with NEP 2020 and the National Curriculum Framework for School Education 2023. CBSE has also introduced Computational Thinking and Artificial Intelligence resources for Classes 3 to 8. This combination of market scale and a clear policy direction creates a broad opportunity for schools to move from experimenting with individual AI tools towards more structured, institution-wide adoption.
11. The company evolved from Digital Ready into AI Ready School in 2025. What changed in the business and product strategy behind that transition?
Digital Ready, which I founded in 2011, trained over 4,000 students across 125+ batches, but it was fundamentally a training business, teaching digital and technology skills to students as a supplementary program. AI Ready School is a different kind of company: instead of training students on AI from outside the school system, we became the operating system schools run their entire teaching and learning process on, from within.
That’s a shift from a services and training model to a platform model built around five integrated products spanning academics, skills, operations, safety and future readiness rather than a course curriculum. It reflects a broader belief I’ve come to over 25 years in this space: teaching students about AI is no longer enough when AI is about to be woven into the curriculum itself starting Grade 3 under NEP 2020. Schools now need AI built into how they teach, not offered as an add-on class.
12. You are targeting 500 schools across India by 2027. What will AIRS need to achieve to make that scale meaningful rather than simply increasing the number of schools onboarded?
Scale without evidence is just a bigger number, so the priority has to be finishing what we have started with AIRS Research, including the 100-school national study and its report, which will launch in Delhi on January 28, 2027. That is what turns a growing school count into a growing school count backed by India-specific, evidence-based findings rather than distribution for its own sake.
The second piece is how we onboard, not just how many schools we onboard. Our process is deliberately structured in four stages, starting with consultation, demo and pilot, followed by solution design and proposal, agreement, and finally implementation with training. We describe ourselves explicitly as partners rather than vendors because the role goes beyond selling software or hardware. It involves working with a school to make it AI-ready and then maintaining that readiness over time. Meaningful scale means that this structure holds at school 500 in the same way it does at school one, with every school going through a genuine pilot and proper training rather than a shortened version of the process simply because the volume is higher.
The outcomes also have to travel. The kind of gains seen in the B.P. Pujari Government School case study, including a 34% increase in final scores and a 77% improvement in analysis-level cognitive tasks, need to be demonstrated consistently across a much larger and more varied set of schools rather than remaining a single result that can be cited. That is the real test of whether reaching 500 schools represents meaningful growth or simply a bigger number.
13. Mars, Morpheus, Zion, NEO and Matrix all appear to take inspiration from the Matrix films. Is that intentional, and what is the thinking behind these names?
Completely intentional. The Matrix, as a story, is about a moment where a person is given the tools to see the world more clearly and think for themselves rather than accept the reality handed to them. That’s almost exactly the shift we want AI to create in a classroom. Mars is the personal companion that helps a student see what they know and don’t know. Morpheus is the guide who equips the teacher. Zion is the base of tools and resources. NEO is where the training turns into real capability and action. And Matrix, fittingly, is the infrastructure layer everything runs on.
There’s also a simpler reason: those names are memorable, and they signal something important about our intent, as we’re not trying to build a passive answering machine. We’re trying to build the thing that helps students and teachers wake up to how AI actually works, and use it with agency rather than dependency.
The names are a small detail, but they say something true about the philosophy underneath the product.
Beyond the AI Tool
What comes through most clearly from the conversation is that AI Ready School is not positioning its product simply as another generative AI application for classrooms. Its larger proposition is that schools need to rethink how AI fits into the institution as a whole, from the way teachers prepare lessons and assess students to how learners interact with AI and how schools manage the underlying infrastructure.
That proposition will ultimately depend on what happens beyond individual demonstrations and pilots. AIRS is attempting to address that question through its 100-school research programme, while its planned expansion to 500 schools by 2027 would put the company’s model across a considerably wider range of schools and educational contexts.
For schools, the practical question is therefore less about whether AI will enter the classroom and more about how it will be introduced. AI Ready School’s answer is an integrated system built around teacher control, personalised learning, local infrastructure and student agency. The company’s next phase will provide a larger test of whether that model can translate from individual implementations into a broader approach to AI adoption across Indian K-12 education.
