AdaptEd AI

AdaptEd AI: Adaptive Education for Every Mind AdaptEd AI is revolutionizing early learning disability detection by making professional-grade dyslexia screening accessible to every family. Currently, 1 in 5 children (20%) have learning disabilities, yet the average age of diagnosis is 9 to 12 years old, years too late. By the time most children are identified, they've already experienced years of academic struggle, diminished self-esteem, and fallen significantly behind their peers. Early intervention before age 7 reduces special education needs by 60% and dramatically improves long-term outcomes, but traditional assessments cost $2,000 to $4,000 with months-long waitlists, making them inaccessible to most families. Our mobile application leverages Microsoft's Azure AI services to provide immediate, affordable, evidence-based screening that parents can use at home. Children simply read a grade-appropriate passage aloud on a tablet or smartphone. Our system, powered by Azure AI Speech's Pronunciation Assessment API, analyzes reading patterns at the phoneme level, detecting critical indicators like letter reversals, consonant blend difficulties, fluency issues, and accuracy problems. Azure OpenAI Service (GPT-4) then generates personalized, actionable learning plans tailored to each child's specific needs, providing parents with concrete daily activities, classroom accommodation recommendations, and guidance on when to seek professional evaluation. What sets AdaptEd AI apart is our comprehensive approach. We don't just screen, we support. Our progress tracking dashboard uses data visualization to show improvement over time, celebrating milestones and keeping families motivated. Our teacher portal enables educators to monitor students whose parents have granted access, creating a bridge between home and school interventions. This collaborative approach ensures children receive consistent, targeted support across all learning environments. We're specifically built for Microsoft's AI ecosystem. Azure AI Speech provides the sophisticated pronunciation assessment capabilities that form our technical foundation. No other cloud provider offers comparable phoneme-level reading analysis. Azure OpenAI Service enables us to generate nuanced, evidence-based recommendations that adapt to each child's unique profile. Azure Cosmos DB ensures we can scale globally while maintaining low-latency access to assessment data. Azure Blob Storage securely handles audio recordings with COPPA-compliant privacy controls. This isn't a cloud-agnostic application. Azure AI is core to our value proposition. Our go-to-market strategy targets three segments: direct-to-consumer (parents via app stores and social media), educational institutions (schools and tutoring centers seeking affordable screening tools), and partnerships with pediatricians and child development specialists who can recommend our app during well-child visits. The total addressable market is massive. There are 50 million K-5 students in the US alone, with 10 million new children entering kindergarten annually who could benefit from early screening. We're currently in MVP development for the Microsoft Imagine Cup 2026 competition, with plans to launch publicly by summer 2026. Azure credits will accelerate our development by enabling extensive testing of Azure AI Speech and OpenAI Service across diverse child populations, optimizing our algorithms for accuracy, and building the robust infrastructure needed for our Imagine Cup demo and subsequent public launch. We're not just building a product. We're building a movement to ensure every child's learning differences are identified and supported early enough to change their entire educational trajectory.

Gautam Raju and Suhas Reddy are Computer Science students at Northeastern University. We're passionate about using AI to solve real problems that affect millions of families. We met during our first year at Northeastern and quickly realized we work well together. Gautam focuses on backend systems and AI integration, while Suhas handles mobile development and user experience. Between us, we've built several projects together, and we've learned how to divide work efficiently and ship products quickly. The idea for AdaptEd AI came from conversations with friends who are teachers and parents. We kept hearing the same story: kids struggling with reading, parents feeling helpless, and assessments being either too expensive or too slow. When we discovered Azure's Pronunciation Assessment API, we realized we could actually build something that addresses this gap. Not just as a school project, but as something that could genuinely help families. At Northeastern, we've taken courses in machine learning, cloud computing, and human-computer interaction. We've seen how powerful Azure's AI services have become, especially for natural language and speech processing. The Imagine Cup gives us a chance to prove that students can build production-quality applications that solve meaningful problems. We're realistic about what it takes to build something useful. We know we need to test extensively with real families, iterate based on feedback, and ensure our assessments are accurate enough to be trusted. That's where Azure credits become critical. Every API call costs money, and we need thousands of calls to test our algorithms, validate our approach, and build confidence in our results. We're not looking for credits to experiment aimlessly. We have a clear development roadmap, specific milestones, and a commitment to launch this publicly. As a two person team, we move fast. We make decisions quickly, write code daily, and stay focused on what matters: building something that actually works and helps people. We're in this for the long haul. AdaptEd AI isn't just our Imagine Cup project. It's the foundation of something we want to grow into a real company that serves families who need better access to educational support.