AI and automation glossary.
Plain definitions of the AI, automation and agent terms our clients ask about most. Each one written by engineers who ship the thing.
AI concepts
24 terms
01
Chatbot vs Agent
A chatbot follows fixed rules to provide information based on a script. An AI agent is more capable because it can plan, use external software tools, and perform multi-step actions to finish a task. While chatbots answer questions, agents actively complete work by interacting with your business systems and data.
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What Are AI Evals?
AI evals are structured tests used to measure how accurately and reliably an AI system performs. You run these tests before and after making changes to your software. Evals provide concrete data on performance, helping you identify errors or drifts in logic before your customers ever see the AI output.
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What Are AI Guardrails?
Guardrails are specific rules or filters placed around an AI system to control its behavior. They ensure the AI stays within defined boundaries while performing tasks. By checking inputs and outputs against these constraints, guardrails prevent the system from producing incorrect, biased, or harmful information in your business workflows.
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What Are Embeddings in AI?
What are embeddings in AI? They are lists of numbers that represent the meaning of words, sentences, or images. Computers cannot read text like humans do. By converting data into these numbers, AI systems can group similar concepts together, search for matching ideas, and power smart search features.
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What Are Structured Outputs
Structured outputs force an AI model to return information in a rigid, predictable format like JSON. Instead of receiving conversational text, your software receives clean data fields. This allows your internal systems to read the AI response automatically without human intervention, ensuring data flows correctly into your existing business tools.
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Understanding the Context Window in AI
A context window is the maximum amount of text an AI model can process at one time. This limit includes your prompt, the conversation history, and the generated response. It is measured in tokens, which are small pieces of words. Once you exceed this limit, the AI forgets older information.
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What Is a Large Language Model (LLM)?
A Large Language Model (LLM) is a neural network trained on vast amounts of text. It predicts and generates human language. Modern LLMs do more than write text. They can reason through complex problems, analyze data, and take actions through software tools to automate business tasks.
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What is a Multi-Agent System?
A multi-agent system is an AI setup where multiple specialized agents work together to complete a complex task. Each agent has a specific role, such as searching data or writing emails. A central coordinator agent often manages the workflow, passing tasks between agents until the entire job is done.
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What is a System Prompt?
A system prompt is a set of initial instructions provided to an AI model. It defines the persona, tone, and operational rules the model must follow. By setting these boundaries before any user input occurs, you ensure the AI behaves consistently according to your specific business requirements and logic.
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What is a Vector Database?
A vector database is a specialized storage system that holds data as numerical values called embeddings. Instead of matching exact keywords, it finds information by calculating the mathematical distance between these vectors. This process allows computer systems to perform semantic search and retrieve relevant context for retrieval-augmented generation.
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What Is AI Grounding?
Grounding is the process of connecting an AI model to specific, verified data sources. Instead of relying on the general information it learned during training, the AI looks at your provided documents to answer questions. This ensures the output is accurate, relevant, and based on your actual business facts.
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What is AI Hallucination?
An AI hallucination occurs when a large language model generates text that sounds correct and confident but is factually wrong or unsupported by any real data. This happens because models predict the next most likely word based on patterns, not because they actually understand facts or truth.
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Understanding AI Inference
AI inference is the process where a trained artificial intelligence model runs live data to make a prediction or decision. Unlike training, where the model learns from historical data, inference is the actual execution phase. It is when the AI does the job you built it to do.
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What is an AI Agent?
An AI Agent is a software system built on a large language model that can reason about a goal. It chooses from available tools, plans its own steps, and carries out multi-step tasks with limited human input. This allows businesses to automate complex workflows that require decision-making.
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What is an AI Token?
An AI token is a basic unit of data that a large language model processes. It is a chunk of text, roughly four characters or three-quarters of a word. When you send text to an AI, it breaks the words down into these tokens to read, understand, and generate responses.
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What is Document Chunking?
Document chunking is the process of breaking large text files into smaller, manageable pieces before converting them into computer-readable numbers called embeddings. This allows AI retrieval systems, like Retrieval-Augmented Generation, to search through your company documents and quickly pull out only the most relevant paragraphs to answer a user question.
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What is Fine-Tuning AI Models?
Fine-tuning AI models is the process of taking an existing, pre-trained large language model and training it further on a smaller, specific dataset. This extra training helps the model perform better on a particular business task or adopt a specific writing style that matches your brand voice.
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What is Function Calling / Tool Use?
Function Calling / Tool Use is an AI capability where a large language model detects when it needs external data and outputs a structured request to run a specific tool, database query, or API. This allows the AI to interact directly with your existing business software instead of just guessing answers.
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What is Model Context Protocol (MCP)?
Model Context Protocol is an open standard that allows AI models to connect to external data and software tools. Instead of building unique bridges for every application, MCP provides a common language. This enables AI systems to read your internal databases and interact with your specific business software more easily.
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What is Prompt Engineering?
Prompt engineering is the practice of writing and structuring instructions for large language models to get reliable, accurate outputs. Instead of typing random questions, you design precise inputs with context, examples, and rules. This ensures the AI performs business tasks correctly every single time.
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What is Retrieval-Augmented Generation?
Retrieval-Augmented Generation is an AI technique that connects a large language model to an external database. Before answering a prompt, the model searches this database for facts. It uses these facts to write its response. This process keeps the AI grounded in real data and prevents it from making up false information.
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What is RLHF Reinforcement Learning from Human Feedback?
RLHF reinforcement learning from human feedback is an AI training method. It uses human ratings of different AI responses to reward the model for outputs that people prefer. This process shapes the behavior of the AI after its initial training, making its answers safer, more helpful, and more accurate for real-world business tasks.
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What Is Semantic Search?
Semantic search is a data retrieval method that finds information based on the meaning of a query rather than matching exact keywords. It converts text into mathematical vectors called embeddings. By comparing these vectors, the system retrieves documents that share the same concept, even if they use different words.
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Zero-Shot and Few-Shot Learning
Zero-shot learning happens when an AI model completes a task without seeing any prior examples. Few-shot learning involves providing a small set of examples within your prompt to guide the output. These methods allow your AI agents to handle diverse business tasks without needing expensive or time-consuming model retraining.
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Automation
07 terms
26
What is a Webhook?
A webhook is an automated message sent from one system to another the instant a specific event happens. Instead of waiting for a manual check, the first system pushes data to the second system immediately. This allows different software tools to talk to each other and trigger workflows in real time.
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What is an Agentic Workflow?
An agentic workflow is an automation design where an AI model autonomously plans, executes tasks, evaluates the outcomes, and refines its next steps. Unlike rigid, step-by-step scripts, this iterative loop allows the AI to handle unexpected variables, use external tools, and self-correct until it achieves the desired business goal.
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What Is API Integration?
API integration is the process of connecting two different software systems so they share data automatically. Instead of manually copying information between apps, an API acts as a bridge. It allows one tool to trigger an action or send data to another tool without any human intervention required for daily tasks.
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What is Automation Orchestration?
Automation orchestration is the process of coordinating multiple tools, steps, and AI agents in a specific order. It ensures that complex, multi-part workflows run reliably from start to finish without human intervention. By managing data flow and error handling across different systems, orchestration turns isolated tasks into a unified, reliable business process.
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What Is Human-in-the-Loop Automation?
Human-in-the-loop is a workflow design where a person reviews, approves, or corrects an AI system output at specific points. Instead of letting software run fully unattended, this method keeps a human in control. It ensures accuracy and safety for high-stakes business tasks that require judgment, context, or final sign-off.
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What is No-Code Automation
No-code automation is the process of building digital workflows using visual interfaces rather than writing custom software code. You connect different tools through pre-built integrations to move data and trigger actions. This approach allows business owners to automate repetitive tasks quickly without needing a deep background in computer programming.
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What Is Workflow Automation?
Workflow automation is the use of software to execute repeatable business tasks without human intervention. It replaces manual steps by linking triggers and actions across different applications. When a specific event occurs, the system automatically performs the next required task, ensuring consistent processes and saving time on repetitive daily operations.
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Voice AI
03 terms
33
What is Speech-to-Text?
Speech-to-Text is a technology that converts spoken audio into written text. It is the first step in most voice AI pipelines. This technology takes sound waves from a human voice and translates them into words. Once converted, other AI systems can read, analyze, and respond to the text.
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What is Text-to-Speech?
Text-to-speech is a technology that converts written digital text into spoken audio. It allows software to communicate with users through a synthetic voice. By processing text data, the system generates natural sounding speech patterns. This technology serves as the foundation for automated voice assistants, accessibility tools, and interactive phone systems.
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What is Voice AI?
Voice AI is a technology that lets computers understand and speak human language. Businesses use it to power phone assistants, automated voice bots, and customer call centers. It listens to spoken words, processes the meaning, and responds with a natural voice to handle tasks without human help.
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