AskLens

AskLens is an AI study companion that summarizes text/images, creates quizzes, and tracks your study time with daily & weekly goals—helping you learn smarter and stay consistent.

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Inspiration

The inspiration behind AskLens came from the need for a faster, smarter way to understand and review information. With so much content to read—whether for studying, teaching, or work—it’s easy to feel overwhelmed. AskLens was built to help people quickly grasp key points, generate practice questions, and interact with an AI assistant, making learning and comprehension more efficient and accessible for everyone.

What it does

AskLens is an AI-powered study companion. It summarizes text or images, generates quiz questions, and provides an interactive chatbot for deeper understanding. Beyond AI, it includes a study timer and progress tracker that let students set daily and weekly goals, track their learning time, and stay consistent with their study habits.

How we built it

We built AskLens using Python for backend logic, Groq for fast AI model inference and response handling, and React for the frontend. This stack allowed us to deliver a smooth user experience while leveraging powerful AI features in real time.

Challenges we ran into

  • Balancing speed and accuracy of AI summaries and questions.
  • Managing token usage efficiently to control costs.
  • Designing a frontend that could handle real-time responses without lag.
  • Seamlessly integrating the study timer and progress tracker into the app workflow.

Accomplishments that we're proud of

  • Creating a functional prototype that connects multiple AI features in one app.
  • Successfully combining summarization, quiz generation, and chatbot features into a single workflow.
  • Building a clean and engaging UI that makes studying more interactive.
  • Adding goal tracking tools to make the app not just smart, but also habit-building.

What we learned

While building AskLens, we learned how to effectively use APIs and manage token usage for AI. We also explored specialization techniques like fine-tuning and transfer learning to adapt models for specific tasks. On the frontend, we gained experience in handling real-time AI interactions smoothly and improving user engagement.

What's next for AskLens

Next, we plan to:

  • Add personalized learning paths that adapt to a user’s progress.
  • Provide PDF exports and flashcards for offline revision.
  • Expand analytics to show long-term learning trends.
  • Experiment with multi-language support to make AskLens accessible to a global audience.
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