The global adoption of Large Language Model (LLMs) is faster than ever before, highlighting the disruptive nature of generative AI. Based on LLMs and related technologies, such as vector databases, generative AI has been extensively explored and practiced in various industry scenarios and cases in areas such as customer experience, employee productivity and creativity, and business operation processes.

Provide users with the tools to streamline the model development process. Users can automate data processing with simple operations, a variety of pre-built models to meet different similar learning tasks, and built-in visualization tools to help users understand data features, model performance, and training progress. In the case of security compliance, users can deploy models to the production environment or cloud platform with one click.

Provide an unified data management platform to protect sensitive data with risk and compliance classification, helping organizations achieve their data management goals. Unified management of unstructured data such as enterprise videos, images, audio, and text, as well as structured data such as tags and dates, to achieve multimodal retrieval.

It provides a powerful data insight platform, including powerful data pre-processing functions and advanced analytical modeling and visualization functions, to help users intuitively understand data and analysis results through charts, reports, and other forms. It also automates the generation of regular data reports and insights to generate leads, optimize existing processes, and drive business growth.

LLMs technology is used to assist in in-depth understanding of text content and context, and help users complete tasks such as public opinion judgment, rapid generation of summaries, multi-text comparison, text classification, sentiment analysis, machine translation, question and answer system, text summarization and content creation. Combined with ASR technology, enterprise services can quickly build their own voice service assistants.

Computer vision technology is used to process and understand image and video data, including object recognition, image segmentation, face, fingerprint and palmprint recognition, to achieve intelligent monitoring, image search, product detection, personnel comparison and other applications.

Use large models to empower education and employee training and realize intelligent education that teaches students according to their aptitude and is full of warmth. Through processing text, audio, video, image and other information with large models, targeted education plans are formulated, and can solve the puzzles and difficulties of learners, provide detailed answers in an interactive form, and give immediate emotional responses.