# Overview Tutorials are organized around real application goals. They guide you through a repeatable path from data ingestion and processing to validation and application output. Each tutorial provides prerequisites, fixed steps, and completion checks for your first hands-on experience with an MOI scenario. ## Choose an application scenario Start with a clear outcome, then follow the tutorial through the complete workflow. ```{raw} html

13 tutorials

About 10 minutes Complete Your First AI Q&A with Sample Data Use an English sample paper to create a knowledge base, ask a question, and verify the answer against its source. Quickstart Knowledge base AI Q&A About 10 minutes Create and use your first agent Use natural language to create a project weekly report assistant, confirm the proposed configuration, and test it in your first conversation. Agents Natural language Quickstart About 20 minutes Create an expense audit agent with a finance skill Import an expense audit skill, create a reusable audit agent, and use sample records to verify its risk findings. Skills Expense audit Agents About 15 minutes Draft and submit GitHub issues with an agent Connect a GitHub tool instance, ask an agent to draft an issue, and submit it to your chosen repository after confirmation. GitHub Tools Agents About 15 minutes Create Your First Knowledge Base from a PDF Upload a PDF, parse and index it, then verify the original text with a cited answer. PDF RAG Citations About 15 minutes From a Local Excel File to NL2SQL Questions Import Excel into a data table and ask for sales and order metrics in plain language. Excel NL2SQL Data questions About 25 minutes Improve knowledge base query accuracy with semantic configuration Import sales orders from CSV, configure metrics, business rules, and constraints, then compare the query results before and after configuration. Semantic configuration NL2SQL Metrics About 15 minutes Configure RAG semantics for document Q&A Import a customer support SLA document, configure a standard RAG question and answer, and repeat the same question to verify the response. RAG Standard Q&A Knowledge base About 30 minutes Prepare multimodal RAG data in batches with a workflow Use a system template to process documents with text and images in bulk, build both indexes, and verify answers across documents. Multimodal RAG Workflow Batch processing About 15 minutes Transcribe audio in batches with a workflow Use the transcription template to process meeting, feedback, and interview recordings in bulk, then inspect the transcripts in Catalog. Audio Transcription Workflow End-to-end scenario Extract key information from S3 engineering documents in bulk Batch-process large collections of existing S3 engineering files, such as borehole logs, and extract identifiers, depth, and other fields for downstream storage, quality checks, and reporting. Batch import Workflow Structured extraction About 15 minutes Create a Team Workspace and Invite Members Create an isolated project workspace, invite colleagues, and assign roles by responsibility. Workspace Collaboration Permissions About 60 minutes Evaluate multimodal RAG with reference answers Add synthetic text, web snapshots, and images to a knowledge base, then use a fixed question set to verify answers, citations, and no-answer boundaries. Multiformat sources RAG evaluation Citation review
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