The next generation of knowledge management

Knowledge management, despite its moderate success after over 40 years of growth, has never completely fulfilled the promise of an intelligent organization. According to Gartner, the worldwide market for knowledge management will reach $1 trillion by 2026. With the advent of remote work and online collaboration, the demand for sophisticated knowledge management is growing. However, current market solutions typically only offer a single function, such as separate collaborative documents, knowledge storage, multi-dimensional tables, etc., which makes information storage disorganized and collaboration inconvenient. Knowledge upload, categorization, labeling, auditing, and others need more manual participation, resulting in increased costs; Furthermore, there is a shortage of intelligent knowledge services for work situations, such as intelligent suggestion mechanisms based on postings, procedures, or user behavior. Knowledge is frequently held statically in the knowledge base, and there is no push mechanism for business-related skills. Even with the push method, the granularity of information is frequently enormous, making it difficult to exploit and develop, and evaluating the reuse value of knowledge is problematic. For many businesses, the building of knowledge management is not from scratch; the business has already developed several IT systems (such as OA, document management, PDM, project management, quality management, scientific and technological achievements database, etc.), These decentralized systems amass a large number of potential knowledge assets, but lack of adequate means of knowledge collection and processing, enterprises rarely establish global knowledge classification ontology, making it difficult to quickly collect and associate relevant knowledge from various dimensions such as specialty, process, post, product, etc.

Another trend to keep an eye on is the growing use of artificial intelligence for office collaboration, especially after the success of ChatGPT. However, the current models of artificial intelligence have issues such as information bias and a lack of transparency.?In fact, a key issue today when you build AI-based apps is that you need to plug in multiple APIs and prompt engineers to build generative models for text and images in a way that bundles them together to build a more complex app.

As the next generation of knowledge management and collaboration platforms, Sophia Intelligence is committed to developing an all-encompassing knowledge and collaboration integration tool. It enables users to complete automatic knowledge search and extraction, semantic retrieval, intelligent recommendation, mining and analysis, knowledge reasoning, intelligent Q&A, tracing back to the original documents, linking experts to real-time interactive knowledge exchange, and transforming document search and query into a multi-scene intelligent application. Rather than relying on individual models tailored to specific tasks or domains, our multi-modal models can handle different modalities simultaneously by activating only the model pathways necessary for a given problem. We will use blockchain-based distributed storage technology to ensure the integrity, security, accuracy, and immutability of the data.

In today's highly competitive market, our products will revolutionize?traditional knowledge management methods, vastly increasing the efficiency of small businesses and making knowledge management more efficient, accurate, and secure.?