Action task – Action tasks collect, modify, and post information in systems of record, like scheduling an appointment, searching for a product, or updating critical information.
Administration & analytics – The Kore.ai Platform provides enterprise grade visibility and control of all enterprise bots, user groups, and security, as well as a commitment to compliance in even the most highly regulated areas like healthcare and financial services. Learn more.
Alert task – Alert tasks deliver timely, relevant, and personalized information to customers and employees directly from enterprise systems. Bots poll the system for user requested updates in real-time.
API – An API, or Application Programming Interface, is a set of definitions, protocols, and tools for building application software. It helps developers by essentially providing the building blocks for a program.
Artificial Intelligence (AI) – AI is the development of computer systems that are able to perform tasks that normally require human-like intelligence, like decision making, speech recognition and understanding, translation between languages, and more.
Auto-NLP – A term we use at Kore.ai to describe our synonym-based approach to natural language processing. It allows chatbots to communicate understand intent variations right out of the gate, thus being speech enabled “automatically”
Automatic Message Formatting – The pre-programmed responses for tasks built into Kore.ai’s NL engine.
Automated Speech Recognition (ASR) – Our Platform includes an Automated Speech Recognition Engine to enable bots to process voice-driven interactions and communicate outside of traditional text-based interfaces.
Amazon Web Services (AWS) – A subsidiary of Amazon.com which provides on-demand cloud computing platforms to people and enterprises.
Bots (also see Chatbot) – Short for a computer program that acts as an intelligent intermediary between people, digital systems, and Internet-enabled things
Bot Builder Tool – Kore.ai’s web-based Bot Builder allows enterprises to customize chatbot use cases, channels, tasks, security, and more. It also provides a framework in which developers can design, test, and deploy chatbots in a consistent process at scale.
Bot Framework – A framework is a skeleton that provides some basic building blocks and generic functionality for building chatbots (like ML/ NLP or a Dialog Builder), but requires additional user-written code or other third-party services (to match the functionality of an actual platform). Frameworks often are composed of piecemeal components from different vendors.
Bots Platform – Kore.ai’s Platform is the only enterprise-grade chatbot platform offered as a SaaS which gives enterprises every component necessary for designing, developing, deploying, and managing AI-rich chatbots.
Bot Connector – For enterprises with systems behind firewalls, the bot connector is a tool that allows you to securely access the data in those systems for use in a bot.
Bot context – User or task information that is captured at the bot level and can be used in context with some or all of the users of that bot.
Channel – A channel is another word for any of the various communication platforms where a bot can live such as SMS, email, mobile apps, websites, messaging apps and more.
Chatbot – Short for a computer program that acts as an intelligent intermediary between people, digital systems, and Internet-enabled things. Find out more about chatbots with our Bots 101 guide.
Chat logs – Histories of all recorded human-to-bot interactions.
Cisco Spark – Cisco’s all-in-one communication platform, which is also a supported channel for the Kore.ai bots and an integration partner for chatbot development.
Cloud (or Cloud computing) – Internet-based computing that provides shared computer processing resources and data to computers and other devices on demand.
Cloud Connector – Provides an agent that runs behind your enterprise firewall that acts as a bridge to facilitate secure data exchanges between on-prem systems and Kore.ai’s cloud based infrastructure.
Component reusability – The ability for developers to use components they’ve already built in the Bot Builder, like APIs, synonyms, tasks, etc. and apply them to other bots.
Context (see also, Bot Context, Enterprise Context, Session Context, User Context) – The information that a chatbot pulls from a conversation with a user that it can leverage when performing tasks. Contextual data can vary in importance, utility, and lifespan.
Conversational Commerce – A term coined by Chris Messina in 2016, which is another way of describing how digital economies will be driven by text and voice based interfaces and experiences.
Conversational UI – Another way of describing text and voice-based interfaces, which don’t require graphical elements for use, like Amazon’s Alexa or Apple’s Siri.
Cognitive Services (aka Conversational and Cognitive Services) – A collection of separate APIs, SDKs, and services (that run on a cloud infrastructure like Azure) which developers can use to build intelligence into apps and/or to construct a chatbot that can leverage AI capabilities. Unlike a platform, charge is typically separate for each service and each bot created.
Data retention – The continued storage of an organization’s data for compliance or business matters.
Deep learning – An area of Machine Learning that is based on learning data representations as opposed to task specific algorithms.
Deployment – The process of publishing a bot to communication channel where it will be engaged by users.
Dialog task – Dialog tasks are advanced tasks that developers design with logic-driven business processes and pre-established workflows. Bots key off the primary request intent to accomplish the task at hand, then go above and beyond to execute sub-intents and additional workflows.
Dialog Builder – The Kore.ai Dialog Builder gives designers and developers the flexibility to manipulate the entire dialog process of a bot interaction and string together complex workflows in a GUI-based tool.
Ecommerce – Any monetary transaction conducted on the internet.
Ediscovery – Any process in which electronic data is sought, located, secured, and searched with the intent of legal use. The Kore.ai Platform supports e-discovery.
Email – A supported channel for Kore.ai bots.
Encryption – The process of converting information or data into a code, especially to prevent unauthorized access.
End-to-end – A way of describing the Kore.ai Bots Platform which signifies that it includes all the component features to take enterprises from the very beginning of the chatbot development process, through deployment and management.
Enterprise analytics – The central dashboard within the Kore.ai Platform where administrators can get visibility into key metrics, pull detailed reports, and track bot usage (i.e. number of executed tasks, most popular channels, most active users, user enrollment, etc.)
Enterprise bots store – A bot store that an enterprise sets up for a select group of users to access any custom built bots.
Enterprise-grade – A way of describing all of the components and capabilities of the Kore.ai Bots Platform that are specifically designed to match the highest enterprise standards, including administration, analytics, security, compliance, and more.
Enterprise context – Information that represents company-wide rules and standards that apply to all users and bots, such as a company travel policy, or expense limits.
Entity – Entities are the fields, data, or words the developer designates are necessary for a chatbot to complete the user’s request. An entity could be a date, a time, a location, a description or any number of things.
Entity extraction – This is the process by which the Kore.ai NL engine identifies words from a user’s utterance to ensure all available fields match the task at hand. If the chatbot needs an entity to complete the task after initial extraction, it will prompt the user for it.
Facebook Messenger – A supported channel for chatbots built on Kore.ai’s Bots Platform, primarily used when companies build bots for end customers.
FAQ – The primary data source chatbots use to pull information to complete knowledge tasks. Coming soon to the Platform will be the ability for website and data based knowledge and document-based knowledge.
Framework – A framework is a skeleton that provides some basic building blocks and generic functionality for building chatbots (like ML/ NLP or a Dialog Builder), but requires additional user-written code or other third-party services (to match the functionality of an actual platform). Frameworks often are composed of piecemeal components from different vendors.
Fundamental Meaning – Fundamental Meaning is an approach to NLP that’s all about understanding words themselves. Each user utterance is broken down word-for-word to search for intent (what the user is asking it to do) and entities (the necessary data needed to complete a task). Learn more about this approach and the Kore.ai NL engine.
Glip – A supported channel for chatbots built on Kore.ai’s Bots Platform.
Graphic User Interface (GUI) – A visual way of interacting with an app or system, such as buttons, images, windows, icons, menu forms, and more.
Hosting – Enterprises have the choice of hosting the Kore.ai Bots Platform on prem or in the cloud via AWS.
Information and Communication Technologies (ICT) – ICT refers to technologies that provide access to information through telecommunications. It is similar to Information Technology (IT), but focuses primarily on communication technologies. This includes the Internet, wireless networks, cell phones, and other communication mediums.
Information task – Information tasks lookup data or pull reports based on specific parameters and quickly return easy-to-consume results that are convenient for users.
Interface – A shared boundary across which two or more separate components of a computer system exchange information.
Intelligence (see also Platform Intelligence) – All the capabilities provided to developers who use the Kore.ai Platform to create AI-powered chatbots including how to use contextual data, memory, NLP, machine learning (both supervised and unsupervised), sentiment analysis, and more.
Intent – The few essential words that describe what the user wants the chatbot to do, usually a verb and a noun such as: Find an ATM, Create an event, etc.
Intent recognition – The process by which Kore.ai’s NL engine analyzes the structure of a user’s command to identify each word by meaning, position, conjugation, capitalization, plurality, and other factors to correctly match the user’s intent to task at hand.
Interaction – Any text-based or spoken communication between a human and a chatbot.
Knowledge task – Knowledge tasks take user questions and query a pre-defined set of information to rapidly find the right answers, such as business hours of operation or specific policy questions.
Kore.ai – Founded in 2014 in Orlando, FL to help enterprises build and use conversational, intelligent chatbots for a variety of use cases. Learn more about Kore.ai
Live agent handoff – The ability of a chatbot to seamlessly take a conversation from any channel and bring in a human agent. This function is especially useful for areas like service and support and ITSM.
Location Services – Location services can be used to build location dependent tasks for greater accuracy.
Logic programming – A type of programming which is largely based on formal logic and is the building block for complex chatbot dialogs and workflows.
Machine Learning – Using algorithms, patterns, and training data, machine learning allows computers to find hidden insights without being explicitly programmed. Learn more about the way Kore.ai uses machine learning for natural language enablement.
Managed Services Provider (MSP) – Most often an IT provider that manages and assumes responsibility for providing a defined set of services to its clients either proactively or as the MSP determines that services are needed. They typically offer a range of services such as network maintenance, hardware repair, help-desk, email management, and anything else that requires a day-to-day administrator to keep running. They may need to purchase technology from a third-party provider, a cost which is bundled with their services and passed on to their end customer. MSPs operate on longer-term annual or multi-year contracts, and the tenure of their relationship is open-ended.
Memory – Bots can remember actions, data, and contextual details to maintain conversation continuity and take helpful actions. The developer can designate how long the bot remembers information as either short term or long term memory.
Message Broker – Consumes all user inputs and system outputs, standardizes for a common messaging paradigm, and redirects to the appropriate endpoints.
Message Store – Stores messages between users, bots, and systems and automatically logs and categorizes message successes and failures.
Microsoft Teams – A supported channel for chatbots built on Kore.ai’s Bots Platform.
Middleware – The Kore.ai Platform Middleware contains the Message Broker, Message Store, and built-in encryption to create a flawless conversational experience by ensuring messages are received, secured, and exchanged in real time.
Mobile SDKs – A set of software development tools that allow developers to create application for a variety of mobile devices. Also a supported channel for Kore.ai bots.
Multi-layer authentication – A method of access control in which the user must provide several separate authentication factors before being granted access to data. The Kore.ai Platform supports multi-layer authentication for bot access.
Multiple intents – When a user gives a complex request to a chatbot which requires the bot to processes and prioritize two or more intents at once.
Natural Language (NL) – The method by which users can talk to systems in everyday language like text and speech, rather than programming language.
Natural Language Processing (NLP) – The process by which a chatbot or any other system understands and processes requests in common language, rather than programming language. NLP is typically enabled via machine learning, but Kore.ai uses a dual-pronged approach which includes intent recognition and entity extraction.
Natural Language Training – The processes in which you refine a chatbot’s ability to understand and process NL requests, and test accordingly. It can be done by adding synonyms to the chatbot’s vocabulary via the Kore.ai Bot Builder, or training with complete utterances via machine learning. You can learn more about how to NL train a bot by watching How To Build A Chatbot In 5 Minutes.
Neural networks – A computer system modeled on the human brain and nervous system.
Omni-channel (deployment) – The process of building one chatbot that is “channel agnostic” (meaning the bot can live in any channel), and deploying it to the communication channels of your choice. Omni-channel bots can be accessed in more than one place and can carry conversation context across channels.
Patterns – Patterns are word combinations that indicate a certain intent or entity.
Pause & resume – When a chatbot receives a task request while in the process of completing an initial request. The bot can then pause one request, complete the more immediate task, and circle back to resume the request it previously put on hold.
Platform architecture – A visual descriptor of the various Platform features and how they interact with one another.
Pilot – The stage after proof of concept where a chatbot’s tasks are published and the bot is deployed to a select group of users for testing.
Proof-of-concept (POC) – The stage where chatbot use cases are determined and tasks are built to prove the viability of initial use cases.
Public bots store – A bot store that an enterprise sets up with custom bots that can be made available for public users, as opposed to an enterprise bot store which only makes bots available to a select group of enterprise users.
Publish – The process by which tasks are developed, completed, and put into use. Unpublished tasks will not be available for test users, but are still available for configuration within Bot Builder.
Response formatting – The process by which a developer customizes the responses a bot will give during an interaction. Responses can be formatted to be natural language only, or include GUI elements like buttons, forms, images, etc.
Robotic Processing Automation (RPA) – A tool for automating manual, time-consuming, complex, rule-based workflows and functions for back-end IT administrative work. While it may sound similar to AI-chatbots, we explain all the nuances and differences in our whitepaper, Robotic Process Automation Software Robots & Chatbots: What’s Different, What’s Similar, and What’s Next?
SAP Solutions – Bots built by Kore.ai to specifically integrate with SAP’s most popular systems, such as SuccessFactors, Concur, S/4Hana, SAP Hybris, and more.
Sentiment analysis – Beyond completing tasks, Kore.ai built bots can understand a user’s mood throughout a conversation. Our NLP engine scores sentiment based on connotation, word placement, and modifiers. Developers can use these scores to trigger custom flows to improve bot-to-user communication, or bring in human agents as needed.
Service call – Service calls are used to make API requests to third-party web services to push, pull, or manipulate data. The web service unpacks the request and converts it to a command that the application or system can understand in order to complete the task or return the needed data. The platform then receives that message and unpacks it in order to obtain the results of the request. The Bots Platform supports the use of API services to make REST, SOAP, or ODATA requests.
Session – The period of time from when a user engages a bot, to when they disengage with the bot.
Session context – Information specified by a user that is the primary context for a bot to keep in mind during a session.
Skype – A supported channel for chatbots built on Kore.ai’s Bots Platform.
Slack – A supported channel for chatbots built on Kore.ai’s Bots Platform.
SMS – A supported channel for chatbots built on Kore.ai’s Bots Platform.
Smart Bots – A group of functionally specific bots built on the Kore.ai Platform that we designed with quick deployment and time-to-value in mind. These bots, which include Banking, Service & Support, IT Help Desk, Commerce, Sales, and SAP, come NL-enabled and with a pre-determined set of AI-rich tasks. They are also customizable.
Software Development Kit (also see Mobile SDK, Web SDK) – Tools or resources that help developers create websites and apps and customize elements of the UI.
Supervised learning for NL – Through the Kore.ai Bot Builder tool, developers and admins can support supervised learning and evaluate all interaction logs, easily change NL settings for failed scenarios, and use the learnings to retrain the bot for better conversations. Developers can also leverage chat logs to build predictive models and use the outcomes to further define additional proactive alerts, suggested actions, or automated workflows.
Structured data – Information with a high degree of organization that is easily searchable when placed in a database.
Synonyms – Word variations for intents or entities that developers can add to a chatbot’s synonym library to give it a wider and more accurate range of natural language understanding.
Tasks – The different types of simple and complex “jobs” a developer designates the chatbot to perform. A chatbot can perform 5 types of tasks: alerts, actions, information, knowledge, and dialog tasks.
Testing – The step-by-step processes of testing request chaining, intent and sub intent recognition and entity extraction, conversation flow, and more.
Training data – The amount of data, usually in the form of utterances, that is fed to a bot in order to
Twitter – A supported channel for Kore.ai bots.
Use case – The various ways chatbots can be applied for employee and customer facing tasks. Check out our Top 30 defined use cases for chatbots.
User context – Individual user information or preferences that can be shared by all enterprise bots the user will interact with, for example, a home address, payment information, etc.
User experience (UX) – The overall experience of a person using a product, like a website or mobile application. It’s usually gauged by how easy or enjoyable something is to use.
User interface (UI) – The means by which the user and a computer system interact.
Universal bot – A bot that has the power to communicate with other bots to complete tasks on its behalf.
Unstructured data – Unstructured data and documents, in this instance, refers to sources that are typically text-heavy and free-flowing. Such documents or data can still contain dates, numbers, and facts, but they lack a pre-defined data model or structure and overall consistency. The Bots Platform supports semantic search against unstructured data and the training of bots from unstructured documents.
Unsupervised learning for NL – Unsupervised learning for NL can be applied to expand the language capabilities of your chatbot – without human intervention. Unlike unsupervised models in which chatbots learn from any input – good or bad – the Kore.ai Bots Platform enables chatbots to automatically increase their vocabulary only when the chatbot successfully recognizes the intent and extracts the entities of a human’s request to complete a task.
Value Added Reseller (VAR) – A value-added reseller offers third party software and hardware to the end user at a markup, along with some combination of procurement consulting, configuration, and customization services. They generate revenues through a combination of flat-rate fees per license, and billable hours, but their engagement is finite.
Web SDK – A software development kit that allows developers to customize websites, also a supported channel for Kore.ai bots.
Workplace by Facebook – A supported channel for chatbots built on Kore.ai’s Bots Platform, and an integration partner for chatbot development.