The way information is mined determines its value.
As generative AI continues to be popular, companies are increasingly demanding the mining and utilization of internal data.
According to ReportLinker, the global enterprise search market is expected toIt will reach US$6.9 billion in 2028.And as the trend of remote work grows, companies' demand for efficient search and knowledge management is increasing.
In this context, a group of enterprisesAI SearchofStartupsIt also came into being.GleanIt is one of the best among them.
Glean is a startup that uses artificial intelligence to help companies search their own knowledge bases.up to dateRaised $200 million in a funding roundThe financing was led by existing investors Kleiner Perkins and Lightspeed Venture Partners, and Glean’s valuation hasIt rose to $2.2 billion.
Glean said their annual recurring revenue has nearly quadrupled in the past year, and its products and services have been favored by major customers such as Sony Electronics and Databricks.
So how does the simple function of "search" create huge value for enterprises after being enhanced by AI?
1
Silicon Valley Rising Star
Based in Palo Alto, California, Glean was founded in 2019 by former Google search engineer Arvind Jain.
Jain graduated from IIT Delhi, India's largesttop notchAfter graduation, he quickly made his mark in the technology world, working for companies such as Microsoft, Akamai, and Riverbed, accumulating rich experience.
In 2003, Jain joined Google, where he made significant contributions to core projects such as Google Search, YouTube, and Google Maps.
He then co-founded Rubrik, a cloud data management company, and noticed that as the company grew, employees encountered significant efficiency problems in finding and integrating internal information, so he founded Glean to solve the challenges of enterprise information retrieval.
Glean's current main business is to provide search and knowledge management solutions to enterprises by connecting the company's applications and databases.
Glean uses a combination of vector search and keyword search to train customized AI models for each client company based on the client company's language and background, and build a knowledge graph about the company's personnel, content, and interactions.
2
Search Revolution
Glean is an AI-driven enterprise search engine designed to solve the problem of inefficient information retrieval within enterprises.
It can quickly locate and integrate scattered information such as meeting minutes, support tickets, project archives, etc. across more than 300 SaaS products used by the enterprise, greatly improving the speed at which employees can find information.
The power of Glean lies in its ability to provide each employee with personalized search results based on their access rights to company data, making information retrieval within the enterprise both secure and efficient.
During the search process, Glean uses large language models (LLM) to provide AI answers, expert search, and related content recommendations, improving the intelligence and efficiency of search.
At the same time, Glean also provides an integrated workspace where users can manage calendars, view announcements, handle meeting links, etc., improving work efficiency.
To put it bluntly,Glean is equivalent to the enterprisesuperbrain.It provides enterprises with a unified and highly customizable search interface, significantly improving the efficiency of cross-platform data retrieval. It also optimizes the relevance and accuracy of information retrieval through highly customized search results, reducing enterprise knowledge loss.
3
AI Reshapes Knowledge Management
Glean is so popular mainly because it solves several big problems facing modern businesses.
First of all, there are too many online services (SaaS) used by enterprises now, and each service has its own data and information, which makes it a headache for employees to find files.
In addition, as the trend of working from home becomes more and more popular, colleagues cannot meet face to face and communication becomes less convenient, which leads to a lot of important information and knowledge being easily lost.
Glean's technical solutions to these problems are significantly innovative in the field of enterprise search.
Specifically, it not only integrates vector search and keyword search technologies, but also cleverly utilizes large language models to provide users with a search experience that is both personalized and intelligent.
This technological integration not only greatly improves the efficiency of information retrieval, but also makes internal enterprise information and knowledge easier to manage and utilize by building a knowledge graph.
This technological innovation and uniqueness is the important reason why it has attracted attention from the capital market.