Lelu-ai

For a long time research has been scattered, lacked powerful tools and had bad user experience. That ends today! ScholarXIV is a next-gen research platform that comes with a set of powerful tools and features to make research a very insightful and an in-depth experience. It let's you build your own research library, curate papers and share them. It also let's users like, bookmark and comment on each and every paper. But the most powerful feature is the AI research with sandboxes. This bring a whole new aspect of conducting research. The sandboxes let you generate files, run simulations and so much more. ScholarXIV also has a proactive feature called Pulse. In Pulse your recently liked and bookmarked papers are converted into a quick and cross-research article to save you time. Checkout ScholarXIV.com for many more epic features like advanced search, paper selection, content analysis and much more.

The legal landscape in Ethiopia is constantly evolving, making it difficult for anyone to stay updated on the latest proclamations and cassation rulings. Negarit solves this with a 100% AI-based research tool powered by a vast, ever-expanding database. By automating the search across a massive corpus of laws, it provides students, citizens, and lawyers with instant, accurate answers from a source that never goes out of date.

Currently, 90% of Ethiopian restaurants rely on outdated legacy systems or manual pen-and-paper because modern hardware is too expensive. This causes slow table turnover, lost revenue, and major language barriers between front-of-house staff and the kitchen. TableTap solves this by operating entirely in the cloud. It is a 100% hardware-free order management platform where waitstaff use their own smartphones to process orders in native Amharic. These commands are instantly sent to a digital Kitchen Display System, effectively acting as an autonomous digital employee that speeds up service and eliminates order errors without the need for a single piece of proprietary hardware.

A few AI efforts exist for Ethiopian languages (Amharic, Afaan Oromo, Tigrinya, Somali, Sidamo, Wolaytta, and more), but coverage is thin, and most of the 80+ languages are still left out, there's not enough open, high-quality data to build competitive AI for these communities. How: Dataset.ET builds open-source speech, text, and translation datasets across these languages through a community-driven pipeline a Telegram bot collects real contributor audio, with vote-consensus and honeypot QC to keep quality high. Datasets are hosted on Hugging Face, fully open, so more builders can create Amharic-speaking AI and beyond, closing the long-tail gap others haven't reached.