Gartner defines business orchestration and automation technologies (BOAT) as a consolidated software platform that delivers enterprise process automation by enabling capabilities including orchestration of business processes, enterprise connectivity, low code development and agentic automation. A BOAT platform includes a cross section of certain capabilities from different markets such as business process automation (BPA), low-code application platforms (LCAP), integration platform as a service (iPaaS), intelligent document processing (IDP), robotic process automation (RPA), collaborative workflow management and document management. However, this list is not necessarily all-encompassing.
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.