Nikhil Shah@shahnikhilb

ranth AI – Revolutionizing research on ancient wisdom with deeper insights, verifiable references, instant access to scripture summaries, and simplified search across diverse manuscript catalogues

Across libraries, temples, research institutions, trusts, and private collections worldwide, millions of valuable books, manuscripts, journals, and archival documents exist only in degraded PDF or scanned formats. These documents often suffer from yellowed pages, faded text, stains, stamps, handwritten markings, shadows, skewed scans, low resolution, blank pages, and inconsistent formatting, making them difficult to read, preserve, search, or distribute digitally. Despite the growing importance of digital preservation and AI-driven knowledge accessibility, there is currently no scalable and user-friendly platform specifically designed to transform poor-quality archival PDFs into clean, digitally optimized documents while preserving their authenticity. This project aims to build an advanced AI-powered web platform that automatically converts old, damaged, stamped, noisy, or low-quality PDF documents into clean, publication-ready digital PDFs. The platform will enhance readability, remove unwanted artifacts, eliminate blank pages, correct orientation and alignment issues, improve contrast and sharpness, and optionally remove institutional stamps through AI-assisted or manual review workflows. Beyond PDF cleanup, the vision is to create a digital restoration ecosystem that empowers libraries, scholars, publishers, spiritual organizations, and archival institutions to modernize valuable knowledge into accessible, searchable, and professionally presentable digital assets. The proposed system will combine image processing, OCR enhancement, AI-based document restoration, and intuitive web workflows to make large-scale digitization practical, affordable, and accurate. Ultimately, this initiative seeks to bridge the gap between historical knowledge preservation and modern digital accessibility, ensuring that invaluable cultural and intellectual heritage can be preserved and utilized for future generations.

📅 May 11–19, 2026 • May 11 – 19: Online Build Phase. • May 18 (Hybrid Build Day – Online & Onsite) • May 19 (Demos & Awards – Online & Onsite) 🌍 Hybrid event. Join online from anywhere or build onsite at the venue. 🏆 Winners will be announced live on stage at the AI & Big Data Expo North America on May 19 📍 On-site Venue (May 18–19): San Jose McEnery Convention Center, CA, USA 🤝 Join solo or with a team. 🎟 FREE AI & Big Data Expo North America ticket included for participants that are able to join the on-site phase. 🏆Compete for a $10,000 prize pool 🧑‍💻 Apply now to design, prototype, and showcase enterprise-ready innovation.

Build solutions that improve how software is built. Work with an AI that understands your codebase, helping you reduce repetitive work and build with real context. ⏳ Build your project in 48 hours. 🚀 Get hands-on with IBM Bob and explore how AI fits into real development workflows before it becomes standard. 💡 Build tools and workflows that developers would actually use. ⭐ Learn directly from experts throughout the event. 🤝 Join a team or build solo. 💰 Prize pool: $10,000 🧑🏻‍💻 Register before the Kick-Off Stream and start building with Bob.

Grab your ideas, spin up compute, and start building what’s next! Start with $100 in AMD Developer Cloud credits and begin building right away. Get access to hands-on tutorials, workshops, and curated learning resources to help you build faster and go further. To unlock credits and join the hackathon, sign up for the AMD AI Developer Program. 🤝 Go solo or team up — ship something real. 💰 $21,500+ total prize pool & 1 × AMD Radeon™ AI PRO R9700 GPU up for grabs. 📍 On-site Venue (May 9-10): MindsDB SF AI Collective 3154 17th St, San Francisco, California, USA 📍On-site participation is by invitation only. Travel and accommodation expenses will not be covered. 🧑‍💻 Developers, builders, and innovators - bring your boldest ideas and let’s turn them into real AI systems on AMD.