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Agent

An autonomous AI component configured to perform tasks, answer queries, or orchestrate workflows using Lyzr’s framework.

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API (Application Programming Interface)

A set of RESTful endpoints that allow programmatic interaction with Lyzr agents, tools, and services.

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AIMS (AI Management System)

Lyzr’s console for monitoring, managing, and governing agent deployments, usage metrics, and audit logs.

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Audit Log

A chronological record of events and actions taken by agents, users, or systems—used for compliance and debugging.

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Bias Mitigation

Techniques and processes to detect and reduce unwanted biases in AI outputs, ensuring fair and equitable responses.

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Chain of Thought

A reasoning technique where intermediate steps are made explicit in prompts to improve model inference and explainability.

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Connector

A pre-built integration between Lyzr agents and external services (e.g., Slack, Salesforce, Google Sheets) to perform actions or fetch data.

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DAG Orchestration

Directed Acyclic Graph–based workflow execution where tasks run in sequence or parallel based on explicit dependencies.

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Data Ingestion

The process of importing documents, databases, or other data sources into Lyzr for indexing and retrieval.

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Embedding

A numeric vector representation of text (or other data) capturing semantic meaning for similarity comparisons and search.

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Embedding Model

An algorithm that converts input data (e.g., text, images) into embeddings; common examples include OpenAI or Cohere embedding models.

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Fine-Tuning

The process of adapting a pre-trained LLM to a specific task or domain by training on a smaller, task-focused dataset.

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Generative AI

AI systems capable of producing new content—text, images, audio—based on learned patterns from training data.

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Intent Recognition

The process by which an AI agent identifies a user’s goal or purpose from their input to select appropriate actions.

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JSON Schema

A JSON-based format for defining the structure, required properties, and data types of JSON documents or API payloads.

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Knowledge Base

A repository of documents, web pages, or databases that agents query to ground responses in real-world information.

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LLM (Large Language Model)

An advanced neural network model (e.g., GPT, Gemini, Claude) trained to understand and generate human-like text at scale.

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Managerial Orchestration

A dynamic orchestration mode where a “manager” agent decomposes objectives into subtasks and dispatches worker agents at runtime.

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Memory Modules

Short-Term Memory: Stores context for the duration of a single conversation. Long-Term Memory: Persists context across sessions to personalize interactions over time.

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Model-Agnostic Pipeline

Lyzr’s architecture allowing you to swap between different LLMs (OpenAI GPT, Gemini, Claude, Bedrock, etc.) without rebuilding workflows.

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Multi-Agent Workflow

An automated process in which multiple specialized agents interact or run in sequence to achieve complex tasks.

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Orchestration

The coordination of multiple steps, tools, or agents into a single automated workflow to achieve an end-to-end process.

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Parser

A component that processes and structures raw data (e.g., JSON, HTML) into a format suitable for downstream tasks or prompts.

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Prompt

A piece of text given to an LLM that guides it to produce a desired output, such as questions, instructions, or context.

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Prompt Template

A reusable blueprint for prompts with placeholders that can be filled dynamically at runtime with variables or data.

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RAG (Retrieval-Augmented Generation)

A hybrid approach combining information retrieval from external sources with generative models to produce grounded responses.

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Reranker

A module that reorders retrieved results (documents, passages) based on relevance before feeding them into a generative model.

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Role-Based Access Control (RBAC)

A security paradigm where permissions are assigned to roles rather than individuals, simplifying governance and compliance.

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SDK (Software Development Kit)

A set of libraries, tools, and documentation that simplifies integration with Lyzr from programming environments like JavaScript or Python.

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Studio

Lyzr’s no-code visual interface for designing, testing, and deploying agents without writing any code.

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Tokenization

The process of breaking text into smaller units (tokens) that a language model can process efficiently.

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Vector Store

A specialized database optimized for storing and querying vector embeddings for fast semantic search and similarity matching.

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Webhook

A user-defined HTTP callback URL that receives real-time notifications or data from Lyzr agents when specific events occur.

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Zero-Shot

An inference mode where an LLM performs a task without any examples or prior fine-tuning, relying solely on its pre-trained knowledge.

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Few-Shot

An inference mode where an LLM is provided with a small number of examples in the prompt to guide its output for a specific task.

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KPI (Key Performance Indicator)

A measurable value used to evaluate the success of an agent or workflow against business objectives (e.g., accuracy, response time).