Data and Analytics refers to products and services that enable organizations to collect, integrate, analyze, and act on data to drive informed decision-making and business outcomes. This category includes markets that focus on empowering enterprises to manage data pipelines, ensure data quality and governance, extract insights through advanced analytics, and machine learning across structured and unstructured data environments.
Gartner defines enterprise AI search as platforms that enable retrieval and synthesis of information across enterprise repositories. They are a key technology for developing AI assistants and AI agents that scale to enterprise needs using retrieval-augmented generation (RAG). They integrate with a wide range of advanced natural language processing (NLP), machine learning (ML) and large language model (LLM) technologies that are essential to knowledge management processes. They are designed to be customized and tuned for specific domains but often come with prepackaged integrations and experiences for some enterprise applications. Enterprise AI search tools are pivotal tools for humans and machines that need to find information and synthesize it to derive insight, so they can subsequently make decisions and take actions. These platforms connect to a wide variety of data sources, normalize and classify information, index it, and match and rank the most relevant results. Their user experiences are commonly customized and are increasingly used as a platform for building AI assistants for a wide variety of operational use cases. Those building RAG-based systems should consider how to configure enterprise search platforms to deliver AI assistants and, in the future, AI agents.
Enterprise search engines are specialized search tools 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.
Gartner defines the generative AI (GenAI) knowledge management apps/general productivity submarket as technologies that enable companies to better retrieve and contextualize information and insight from their knowledge bases, including enterprise AI search, conversational AI platforms, and productivity tools for communications and content development.
Gartner defines search and product discovery as applications that augment digital commerce solutions to facilitate navigation, filtering, comparisons and, ultimately, selection of products. They provide search (keyword, semantic and visual), merchandising (automation, configuration and curation of business rules) and product recommendations. These applications also provide catalog navigation (including SEO keyword automation and guided selling assistants). Personalization, optimization and analytics capabilities should also be available. Platforms are deployed as SaaS. They provide administrative tooling to enable digital commerce roles (merchandisers, content managers and search specialists) to support customer experiences via no-code. With the emergence of generative AI, conversational search and guided selling assistants are now appearing. Search and product discovery applications can provide the digital customer journey from landing on a website or app to finding the correct product and adding to basket. Search results can be highly visual, using engaging layouts and multimedia. Content other than product information, such as educational information, compliance materials, customer reviews and related news may also be included in search results to engage customers and further support buying decisions.