Introduction to Amazon Quick Suite - An AWS Agentic Service

This demo shows building a self-serve QuickSight dashboard for a sales VP to review last week's performance, reducing back-and-forth with analytics and enabling questions beyond the dashboard.

Create, join, and transform datasets in quick sight by uploading orders, products, and customer data, rename keys to avoid conflicts, and perform left joins to build order management data set.

Build a dynamic dashboard with KPI visuals for total revenue, total orders, and average order value, then use line charts, forecasts, and insights from natural language capabilities.

Learn to create drill down in a report by adding product name under category, then apply region and order status filters to update charts across the sheet.

Create a multi-sheet dashboard with a detailed view and a summary, apply filters across all sheets, and publish the management dashboard with executive summaries, stories, and scenarios.

Explore how Amazon QuickSight generates executive summaries and stories from dashboards, enabling you to publish insights, build narratives, and drive revenue strategies.

Explore how QuickSight scenarios use generative ai for what-if modeling with natural language to analyze revenue impact, customer segments, and price-change scenarios across dashboards.

Discover how topics in QuickSpeed provide a semantic layer over your data set to answer natural language questions and generate charts for readers.

Explore quick chat spaces and external connections in QuickSuite, and watch a demo that contrasts default versus custom agents, shows organizing spaces, data sources, attachments, and 24/7 availability.

Demonstrates building a custom chat agent in QuickSuite, defining a friendly customer support persona focused on orders, troubleshooting, and returns, and configuring prompts, documents, knowledge sources, and actions.

Upload reference documents to a custom agent to tailor responses with your own return policies, warranties, and troubleshooting guides. See how attached data changes answers versus a default agent.

spaces in quicksuite act as a knowledge center for a team, aggregating data and files; attach return policy and warranty guide, then query the space-bound agent for precise answers.

Attach a space to the custom chat agent to expand its knowledge base with documents and a quick site dashboard. Use the space as a knowledge source for customer inquiries.

Demonstrate creating a web crawler, configuring knowledge bases and actions, and integrating Jira with Asana and Confluence using REST, open APIs, and API tokens.

Configure and test a custom agent with Jira and knowledge base integrations, showing issue creation, syncing, and throttling handling.

Explore how Amazon Quick Research enables deep, professional, exportable reports by integrating web, internal, and third-party data, and learn when and how to structure and refine comprehensive research tasks.

Explore a demo use case where SomeCompany Ventures analyzes AIML investment opportunities, using the Amazon Quick Research service to assess market size, growth, competition, risk, and recommendations.

Set up a new research in the quick suite console, define a venture-capital AIML market study goal, and configure prompts, data sources, and a data-driven report plan.

Watch a live demo of an agent compiling comprehensive AI market research from multiple sources, yielding interim AI landscape, investment risks, and IPO trends reports.

Review the final Amazon QuickSuite research report, highlighting executive summary, market size, technology assessment, and competitive landscape. Explore customizable summaries and export options for leadership.

Learn to automate repetitive business tasks with quick flows, using natural language or drag-and-drop no-code actions to create workflows that retrieve data, analyze it, and write results to external systems.

Explore how quick flows automate a retail customer support workflow, from order lookup and shipping status checks to email updates and activity logging.

Build a customer support flow in QuickSuite that takes customer email and order number, retrieves order details, checks shipping status, and generates customer and internal emails plus a summary.

Test and validate customer support flows using run mode, inputting customer email and order number to retrieve order status, generate personalized emails, trigger internal notifications, and schedule automated runs.

Automate a weekly three-page competitive intelligence report using quick flows to streamline competitor research, pricing changes, industry news, and internal sales data for leadership.

Build an automated competitive intelligence flow in Quick Suite using web search, pricing updates, and a research agent to pull dashboard data and generate a three-page report sent to Slack.

Create a new Slack workspace and configure the Quick Suite connector with base URL, client ID, client secret, and redirect URL, then sign in and test the channel post.

Configure and test quick flows to post a Slack summary for competitive intelligence, exploring Dell and HP trends, product launches, pricing, and leadership changes via a multi-step research flow.

See a complete quick suite flow that runs research and builds a competitive intelligence report. It generates a Slack summary and demonstrates automation that posts to a product intel channel.

Explore setting up Amazon Automate in QuickSuite, use Quick Automate for complex ETL tasks, and build a UI agent to fetch Nasdaq and NYSE data for a market summary.

Ingest invoices from the S3 in-progress folder, extract invoice number, amount, and customer name with Textract, and generate an Excel file of unpaid invoices in S3.

Explore the quick automate left pane, featuring UI and custom agents, pro vs fast modes, process flows with loops and if-else, and variable-based output.

Learn to configure Amazon Quick Suite connectors for S3 and Textract within the admin console, assign IAM roles, and integrate them into automated workflows.

Create an S3 bucket in the AWS console, establish three folders: in progress, invoices, and processed invoices, and upload invoices to prepare for automating invoice processing to Excel output.

Demonstrates building an automation to list S3 invoices, extract file names from contents, and write data into an Excel workbook for downstream processing, with logging and debugging steps.

The video demonstrates adding an if-else condition to process only pdf files in S3 response by lowering the file key and ending with .pdf, appending to pdf files list.

Learn to build Textract-based invoice extraction from S3: create an invoice data dictionary, populate an invoice table, loop over PDFs, and save results to Excel and S3.

Demonstrates creating an excel workbook, writing textract-derived unpaid invoice data to sheet 'invoice', saving as xlsx, uploading to S3, and debugging vendor versus customer fields and folder processing.

Build a loop to move processed invoices by copying them to the processed invoices folder and deleting the originals, preventing reprocessing and enabling automated invoice tracking in an Excel sheet.

Rename the automation to invoice processing, commit and deploy changes, schedule a daily trigger at 10 p.m. Eastern Time using cron expressions, and deactivate triggers during testing to control costs.

Receive frequent updates on AWS QuickSuite through announcements and new lectures as features launch. Suggest scenarios to build end-to-end use cases and help expand the course.