Hai News vs Lettria

Hai News is a comprehensive and informative online news platform that provides readers with the latest news and updates from around the world. With a focus on delivering accurate and reliable information, Hai News covers a wide range of topics including politics, current events, business, technology, entertainment, sports, and more.

At Hai News, we strive to deliver news stories that are both engaging and insightful. Our team of experienced journalists and writers work diligently to ensure that our readers are well-informed and have access to high-quality journalism. We provide in-depth analysis and coverage of important events, interviews with key figures, and feature articles that explore various aspects of the news.

One of the unique aspects of Hai News is our commitment to providing diverse perspectives. We believe that it is important for readers to have access to different viewpoints and opinions, and we aim to present a balanced and nuanced portrayal of the news. Through our articles and features, we encourage readers to engage in thoughtful discussions and debates.

In addition to news articles, Hai News also offers a variety of multimedia content such as videos, photo galleries, and interactive graphics. These elements enhance the reader's experience and provide a more immersive way to consume the news.

Lettria builds a graph context layer that turns enterprise documents and databases into ontology-backed knowledge graphs for automation teams. Its Knowledge Studio GraphRAG product parses PDFs, tables, SAP exports, and scanned annexes, then answers multi-hop questions with source citations. Perseus is the developer platform for generating ontologies and graphs without hand-modeling every entity.

Vector RAG tools retrieve similar chunks; Lettria follows explicit relationships across structured and unstructured data. The company publishes benchmark comparisons showing graph agents at 81.7% overall accuracy versus 57.5% for vector agents, plus text-to-graph claims of 30% higher accuracy and up to 400x faster extraction than general LLMs. That trade-off favors regulated teams that need audit trails over quick semantic search.

Finance, healthcare, legal, and engineering groups use Lettria for ESG filings, biomedical literature, contract corpora, and technical manuals. Case studies cite Alfa Laval (+30% extraction accuracy), AP-HP (+60% faster research), and Wisecube processing 108 GB of biomedical text into 500+ monitored classes.