Case Study: The Newsroom achieves faster, style-tailored news summaries with Oxagile's AI LLM solution

The Newsroom builds an AI news aggregator with Oxagile and 100% style-matched summaries

The Newsroom, a news agency, faced the challenge of its journalists spending an excessive amount of time manually sifting through press releases and writing stylistically consistent summaries. To address this, they partnered with vendor Oxagile to develop an AI-powered news aggregation solution.

Oxagile implemented a solution using a fine-tuned Falcon large language model (LLM) via the Hugging Face infrastructure. The LLM was trained using a Parameter-Efficient Fine-Tuning (PEFT) method to precisely mimic any defined text style, enabling it to generate unique and compelling summaries that capture the essence of news items. This provided the news agency with a tailored tool that automates the gathering and summarizing of news stories to meet journalists' specific needs.