The problem Learnify solves

Learnify addresses several critical challenges in the job market and education sectors:

Skill Gap Crisis: There’s a widening gap between the skills that job seekers have and those that employers need. Learnify helps bridge this gap by offering real-time, AI-driven skill analysis, identifying specific areas where users can improve to meet job market demands.

Unsustainable Pricing Models in Education: Traditional learning platforms often require students to purchase individual courses, which becomes costly. With Learnify's one-subscription model, learners gain access to all courses, and tutor compensation is based on watch time, ensuring fair value distribution.

Fragmented Learning Resources: Learners struggle to navigate a fragmented landscape of resources. Learnify consolidates learning materials into a personalized roadmap based on current market competition and individual skill requirements.

Lack of Personalized Learning: Generic, one-size-fits-all courses fail to meet individual needs. Learnify personalizes learning through AI-driven insights, creating a customized educational experience for each user.

Educator-Learner Mismatch: Educators face difficulties reaching their target audience, and learners struggle to find relevant instructors. Learnify's decentralized marketplace connects learners and educators directly, making it easier for both to find the right match.

Opaque Job Market: Job seekers often lack insight into their position relative to competitors. Learnify's AI-powered analysis offers users detailed insights on necessary skills, competitive standing, and career advancement pathways, creating a more transparent and achievable career journey.

Learnify ultimately provides a cohesive, efficient solution to these problems, making career development more accessible, transparent, and personalized.

Challenges we ran into

Integrating AI and Blockchain Seamlessly: Combining AI for personalized recommendations with blockchain for secure, decentralized credential verification was technically complex. Ensuring these two technologies worked together in real-time required extensive research and fine-tuning.

Real-Time Skill Analysis: Building an AI model capable of evaluating user skills dynamically and comparing them to the job market posed challenges in terms of data processing and accuracy. We needed to balance real-time processing with reliable, insightful analysis.

Decentralized Payment and Compensation Model: Implementing the one-subscription model with fair revenue distribution to tutors based on watch time was a unique challenge. Setting up smart contracts to automate payments securely and transparently required careful design to ensure accuracy and trustworthiness.