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Getting Started

What's deepset AI Platform?
- Feature List
- deepset AI Platform and Haystack
deepset AI Platform Status
What's New
Quick Start Guide
Working in deepset AI Platform
Basic Concepts
Updating Settings
- Managing Workspace Settings
- Managing Organization Settings
Third-Party Software

Tutorials

Learn the Basics
Learn More Advanced Features
REST API Tutorials
- Tutorial: Creating a Chat App Through REST API
- Tutorial: Managing Feedback Entries Through REST API

How-To Guides

Working with Your Data
Working with Indexes
Designing Your Pipeline
Evaluating Your Pipeline
Optimizing Your Pipeline
Testing Your Pipeline
Productionizing Your Pipeline
Building with Large Language Models (LLMs)
Building AI Agents
Working with the SDK
Working with Jobs
Managing Access
Using deepset MCP Server

Concepts

Indexes
- PreProcessing Data with Pipeline Components
Pipelines
- Multimodal Systems
Pipeline Examples
- Auto Loan Payment Chatbot
AI Agents
- Agentic Pipelines
- AI Agent
  - Agent State
  - Agent Tools
Document Stores
Pipeline Components
Jobs
Data Flow in deepset AI Platform
Language Models in deepset AI Platform
User Roles and Permissions
Secrets and Integrations

Learn

Building an AI-Based App
- Components of an AI-Based App
- 5-Step Guide to Building a Successful Prototype
Model Context Protocol
Retrieval Augmented Generation (RAG) Question Answering
Document Search
Prompt Engineering Guidelines
Extractive Question Answering
Language Models
- Large Language Models Overview

Outputs

End your query pipeline with an output component.

Output: The output of a query pipeline.

Updated about 2 months ago

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