An enterprise search engine is a specialized search tool designed to help organizations index, search, and retrieve information stored within their internal data repositories. Unlike general web search engines that index and search the entire internet, enterprise search engines focus on the internal data of an organization, which can include documents, emails, databases, intranet sites, and other digital assets or data sources. Modern enterprise search engines often incorporate Natural Language Processing (NLP) and Machine Learning (ML) and AI-powered technologies to enhance their capabilities and improve the search experience. This type of search engine is adept at handling both structured and unstructured data, making it invaluable for diverse use cases such as knowledge management, customer support, and business intelligence. By integrating these enterprise search software capabilities, organizations can ensure that employees have quick and relevant access to the information they need, thereby improving productivity and decision-making.
Generative AI (GenAI) apps use generative AI capabilities for user experience and task augmentation to accelerate and assist the completion of a user’s desired outcomes. Generative AI refers to technologies that can generate new derived versions of content, strategies, designs and methods by learning from large repositories of original source content. When embedded in the experience, generative AI offers richer contextualization for singular tasks such as generating and editing text, code, images and other multimodal output. As an emerging capability, process-aware generative AI agents can be prompted by users to accelerate workflows that tie multiple tasks together. Apart from helping save time and money, generative AI apps help improve branding of businesses by creating more engaging and effective content while also creating more engaging and immersive experiences for customers. Please note that this market is based on Beta research and is continuously evolving. We will be making changes as and when there are new updates.
Gartner defines Insight Engines as follows: Insight engines apply relevancy methods to discover, analyze, describe and organize content and data. They enable the interactive or proactive delivery or synthesis of information to people, and data to machines, in the context of their respective business moments. Insight engines should be viewed as platforms on which applications are provided, developed or augmented by applying the capabilities listed above to specific employee and customer experience use cases. Such applications are provided out of the box by vendors (e.g., intranet or site search), developed through technical partnerships (e.g., search within third-party applications), developed with customers in-house (e.g., expert finder), or developed through integration with third-party applications (e.g., extracting data from documents to support RPA).
Knowledge Management (KM) Software enables a wide variety of operations around documents and files to optimize access and flow of information within an organization. Knowledge Management Software is compatible with multiple file types like documents, presentations, audio-video files, etc. to enable all these operations. Enterprises leverage the software to create a centralized repository of information that traditionally existed in silos. The primary function of the software is to store, retrieve, and share information across the organization in a convenient, safe, and reliable manner. Some Knowledge Management Software also provides some extended functionalities like – File Edit history, access management, and content editing capabilities.