乐鱼（Leyu）体育官网

乐鱼（Leyu）体育官网 is helping clients use Llama鈥擬eta鈥檚 open-source large language model (LLM)鈥攖o solve a variety of business problems. Offering extensive training on diverse data, fine-tuning capabilities, adherence to ethical guidelines, continuous learning, and multilingual support, the model can support a wide range of use cases across industries. Explore the following real-life examples.

Internal Audit Assistant

Client: Global technology and social media company

Virtually every internal audit (IA) team is seeking ways to streamline time-consuming processes, such as preparing initial audit reports and performing ongoing audits of internal control effectiveness.聽These workflows are ripe for augmentation with generative AI (GenAI). A global technology and social media company鈥檚 IA team turned to 乐鱼（Leyu）体育官网 to explore how Llama can support four specific IA use cases: Observation Generation, Report Creation, File Upload Summary and Analysis, and Scope Creation.

乐鱼（Leyu）体育官网 helped deploy a GenAI system that is being trained with historical reports and workpapers provided by the IA department. The goal: provide a smart 鈥渁ssistant鈥� that generates high-quality output aligned with the established content structure and writing style.

Other companies can collaborate with 乐鱼（Leyu）体育官网 and use Llama to explore opportunities to streamline audit report writing, increase content consistency and alignment to prescribed style guides, and empower individual auditors to work more quickly and efficiently.

Loan Summarization

At an American global multinational bank, the wholesale credit team had already adopted natural language processing (NLP) to accelerate extraction of hundreds of data elements per loan document. With the advent of LLMs, they recognized an opportunity to take automation and intelligence to the next level.

The bank worked with 乐鱼（Leyu）体育官网 to deploy a tailored GenAI solution. The vision: use GenAI to empower human reviewers to more quickly and efficiently review and interrogate complex loan applications. We used our defined framework for training and fine-tuning to address complexities and optimize training within a secure environment. Llama demonstrated strengths in enabling generation of sophisticated loan document summaries, which support and streamline business decision-making.

Using Meta鈥檚 open-source LLM, other financial services institutions can increase the speed鈥攚ithout compromising the integrity鈥攐f their highly complex business processes.