Glossary

A comprehensive reference of terms and concepts used in the Twig AI platform.

A

Agent

An AI-powered assistant configured with specific data sources, instructions, and behavior patterns to answer questions and provide information.

Agentic Workflow

A mode where the AI agent can use tools, make function calls, and perform multi-step reasoning to solve complex problems.

API Key

A credential used to authenticate programmatic access to the Twig AI REST API.

C

Cedar Strategy

A RAG strategy that rewrites user queries based on conversation context before retrieval. Balanced speed (~2-3 seconds) and accuracy.

Chunking

The process of breaking large documents into smaller segments for more precise retrieval and processing.

Citation

A reference to the source document used to generate an AI response, providing transparency and enabling fact-checking.

Context Window

The amount of text (measured in tokens) that can be processed in a single request by a language model.

Cypress Strategy

An advanced RAG strategy using query expansion, tier-based retrieval, and automatic reranking. Highest accuracy (~3-4 seconds).

D

Data Source

A repository of information that can be ingested into Twig AI, such as documents, websites, databases, or cloud storage.

E

Embedding

A numerical representation of text that captures semantic meaning, enabling similarity-based search.

Evaluation (Evals)

Automated tests that measure AI agent performance across metrics like relevance, accuracy, and citation quality.

H

Hallucination

When an AI generates information that isn't supported by the provided context or source documents.

I

Inbox

The interface where you review, edit, and improve AI responses to train and optimize your agents.

Interaction

A single question-answer exchange between a user and an AI agent, stored for analytics and improvement.

K

Knowledge Base (KB)

A curated collection of articles, automatically generated from interactions or manually created, that serves as truth data.

L

LLM (Large Language Model)

The AI model that generates responses, such as GPT-4, GPT-3.5-turbo, or Claude.

M

Memory

Conversation history stored to maintain context across multiple turns of dialogue.

P

Pinecone

A vector database service used for storing and searching document embeddings.

Playground

A testing environment where you can interact with AI agents before deploying them to production.

Private Data

Data sources that contain organization-specific information, accessible only to authorized users.

Prompt Engineering

The practice of crafting effective instructions and prompts to guide AI behavior and responses.

R

RAG (Retrieval-Augmented Generation)

An AI technique that retrieves relevant information from a knowledge base and uses it to generate accurate, contextual responses.

Redwood Strategy

The fastest RAG strategy using direct vector search without prompt rewriting (~1-2 seconds).

Reranking

A secondary ranking step that reorders retrieved documents using a sophisticated cross-encoder model to improve precision.

S

Semantic Search

Search based on meaning rather than exact keywords, using vector embeddings to find conceptually similar content.

Session

A continuous conversation context, identified by a session ID, that allows the AI to remember previous exchanges.

SSO (Single Sign-On)

Authentication method that allows users to access Twig AI using their organization's identity provider.

Strategy Code

An identifier specifying which RAG strategy an agent uses (e.g., STANDARD_RAG, INFER_QUESTION, CYPRESS).

T

Temperature

A parameter (0.0-1.0) controlling the randomness of AI responses. Lower values are more deterministic, higher values more creative.

Tier

A priority level assigned to data sources, used in Cypress strategy for organized retrieval.

Token

A unit of text processed by language models, roughly equivalent to 4 characters or 0.75 words.

topK

The number of most relevant documents retrieved from the vector database (typically 5-10 for Redwood/Cedar, 50 for Cypress).

V

Vector Database

A specialized database for storing and searching high-dimensional embeddings, enabling semantic search.

Vector Embedding

See Embedding.

W

Webhook

An HTTP callback that sends real-time notifications when specific events occur in your Twig AI organization.

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For more detailed explanations, see Core Concepts.