How Natural Language Processing Can Unlock The Power of Your Company’s Knowledge Repository

Natural language processing (NLP) capabilities have a come a long way in a relatively short space of time, bringing a range of powerful new tools to the business world. One of the most impactful applications must be the integration of NLP and knowledge repositories. Keep reading to learn why.

Broadly speaking, natural language processing allows businesses to transform their static information repositories into dynamic, intelligent systems that increase information availability and offer a host of associated benefits. Namely…

Enhanced search and retrieval

Businessman touching the natural language processing or NLP virtual screen to chat with the bot and connect to customers on the work desktop.

Traditional keyword-based search functionality in knowledge repositories has its limitations, often yielding inaccurate results. By incorporating NLP technology, however, businesses can leverage far more advanced search algorithms that understand the meaning and context of a query, as well as the intent behind it.

That means more accurate and relevant search results, making it far easier for employees to find the information they need. With less time spent searching, NLP-enabled search in a company’s knowledge repository can significantly increase productivity.

Improved information extraction

Data science and big data technology. Scientist computing, analysing and visualizing complex data set on computer. Data mining, artificial intelligence, machine learning, business analytics.

Extracting information from unstructured data sources the old manual way is time-consuming and error-prone. NLP technology can help to automate such tasks, with the ability to analyze and extract key insights from any of the text sources that have been uploaded to the database. This can save valuable time and resources while ensuring that all information is captured correctly.

Knowledge discovery and insights

An NLP-enabled knowledge repository system can be used to analyze text data to find patterns and relationships that wouldn’t be obvious to a human. This can lead to uncovering hidden opportunities, learning about emerging market trends, competitor intelligence, or revealing customer sentiment. With NLP, a new level of insight becomes possible, making it easier for data to drive decision-making.

Something to keep in mind: research from McKinsey & Company found that data-driven organizations are 23 times more likely to acquire customers, demonstrating that initiatives to make data more accessible are sure to pay off. In fact, they can make all the difference, especially in a tough economic environment.

Intelligent chatbots and virtual assistants

Chatbot artificial intelligence intelligent robot technology AI. Artificial intelligence technology automatically responds to online messages to help customers instantly.

A chatbot with NLP capabilities trained on a company’s knowledge repository becomes a powerful business tool with a number of applications. It allows a business to provide personalized and immediate support for both customers and employees. Since an NLP-powered chatbot can “understand” a user’s query, it can provide more relevant responses. It can take the pressure off support teams by handling product queries or assist the HR department by responding to information requests such as questions about company policy. It can even help the IT department with troubleshooting. What’s more, a smart chatbot can be available around the clock.

Compliance and risk management

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Complying with regulations is always paramount but an NLP-enabled knowledge repository can be a big help since it can be used to automatically analyze and categorize large volumes of legal documents, contracts, and industry-specific regulations. It can quickly identify and extract relevant information to help decision-makers ensure compliance, mitigate risks and streamline auditing processes. This can help to reduce the chances of legal or regulatory issues, which can be hugely costly (an average of US$4 million in revenue, according to research from the Association for Information and Image Management).

Continuous learning and improvement

Natural language processing models combine rule-based modelling for language with machine learning and deep learning models, which means an NLP-powered knowledge repository can learn from interactions with users and feedback. The NLP algorithms can therefore improve over time to provide more accurate and relevant responses, better recommendations, and improved user experiences.

Empower your knowledge repository

By integrating natural language processing capabilities into your company’s knowledge repository, you open a world of value with tools for practical applications that can save your organization time and money, deliver invaluable insights, and ensure that every team, from legal to marketing, always have the information they need at their fingertips. We call such a tool Cody AI, and it’s reshaping the way companies operate in profound ways. You can discover what it can do first-hand by starting your free trial today.

Author

Oriol Zertuche

Oriol Zertuche is the CEO of CODESM and Cody AI. As an engineering student from the University of Texas-Pan American, Oriol leveraged his expertise in technology and web development to establish renowned marketing firm CODESM. He later developed Cody AI, a smart AI assistant trained to support businesses and their team members. Oriol believes in delivering practical business solutions through innovative technology.

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