Conversational AI – Powering the Future of ‘Search’



Launched in November 2022, Open AI’s Chat GPT garnered significant attention for its articulate and detailed responses to user queries despite occasional inaccuracies. It has changed how people use AI to complete their tasks. Earlier, people used Google for information. Now, many use Chat GPT instead, marking a significant shift in how people seek answers using the Internet. This has empowered Google and Microsoft to use AI in their respective search engines and offer a better knowledge discovery experience.

AI-Enhanced Search – What’s Different?

AI-enhanced search engines offer intuitive and personalized experiences by understanding user intent, correcting errors, and suggesting relevant results. They utilize advanced Natural Language Processing (NLP) algorithms to interpret conversational queries accurately, enabling users to search with simpler keywords and leading to precise results. Additionally, these engines excel in handling voice queries, providing seamless experiences by interpreting spoken language and comprehending context. Automating tasks such as indexing and categorizing content enhances search efficiency, allowing websites to manage vast amounts of information effectively. AI-enhanced search can be crucial in sharing and assimilating knowledge within closed knowledge systems.

Utilizing AI-Enhanced Search in a Closed Knowledge Repository

AI-enhanced search in a closed knowledge repository works differently. Content discovery is streamlined and enables personalized experiences, optimized content, and context-specific results. Semantic search and effective tagging provide highly accurate information without the need for extensive filtering and analysis and minimizing distractions.

Let us consider that an organization has a knowledge repository with comprehensive information about its policies. An employee wants to find specific information about the organization’s IT policy. A traditional search engine would offer many results such as links to documents, and the employee would have to manually go through these links and identify the suitable document with the information needed.

On the other hand, an AI-enhanced search engine uses conversational AI and revolutionizes information organization, helping users navigate and comprehend the vast volume of available content. It lists search results; if the user does not find a relevant result, the user can interact with the conversation/chat feature built into the search engine to add better prompts and find the correct answer for the query. Thus, conversational and AI-enhanced search unveils novel categories of inquiries that a regular search engine might not have addressed.

Eliminating the Risk Factor

AI platforms undergo training using vast datasets, posing legal risks such as intellectual property infringement. The recent lawsuit between The New York Times and OpenAI highlights such concerns. Legal frameworks are evolving to address ownership and rights issues regarding AI-generated content. Ethical considerations regarding AI usage and the rise of factually incorrect information add further complexity. Organizations using AI tools must navigate these legal and ethical challenges and establish robust validation processes for AI-generated content.

How Does Impelsys Eliminate this Risk?

Impelsys has developed mon’k, a future-ready, SaaS-based platform with military-grade DRM. mon’k is equipped with AI-enhanced search, which makes searching for information intuitive, user-friendly, and efficient.

This AI-enhanced search employs specifically trained Large Language Models (LLMs) to respond to user inquiries. It retrieves pertinent documents and identifies the sources that address the user’s queries. Additionally, it features a memory-based chat module to recall past interactions between the user and the model. Conversational AI comes into play here and makes a difference in the quality of search results.

mon’k offers a high level of security and ring-fences all content so that no external search engine can crawl content stored in it. mon’k uses an in-house LLM (Large Language Model) to train the AI engine, ensuring that the content owned by one organization or publisher is not used for training AI models that others can use.

What Makes Impelsys’ AI-Enhanced Search Different?

  • Safe and secure search environment
  • Valid and verifiable sources
  • Crawlers cannot breach the DRM-protected platform/ecosystem
  • Ensures that the LLM only uses the content available in the knowledge repository


As organizations in the publishing and learning industries transition to closed knowledge repositories or ecosystems for security and IP reasons, the need for a robust platform that offers AI-enhanced search capabilities increases. mon’k by Impelsys bridges the gap in this space with its integrated knowledge suite and secure and efficient content management and delivery capabilities.

Authored by: Abhishek Kumar