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AI4U: Giving AI Agents Real Memory with Oracle AI Database - Retail

About This Workshop

Youtube Video

About This Workshop
Most chatbots explain how to do things. In retail, ask a typical chatbot, “Where’s my order?” and you might get a step-by-step tutorial on how to check tracking or contact support. Agents are different. They act.
In this workshop, you’ll build the four components: tools, agents, tasks, and teams, and review the execution history that proves the agent queried real data. You’ll build agents that can read and write (not just give generic, zero-shot answers) and plan and execute multi-step workflows, including a real item risk assessment and routing process (auto-approve vs appraiser vs senior appraiser based on defined conditions).

You’ll then tackle what makes agents practical in a fast-growing retail operation: memory that persists across sessions (collector preferences, loyalty discounts, past decisions, and policy/reference knowledge), semantic search (searching your data by description), and safety controls like separation of duties plus a complete audit trail of every tool call for compliance.

Your key to being amazing starts here, with an agent that acts instead of explains. No sophisticated ML required, just SQL and a little curiosity.

Workshop Info

2 hours
  • Why agents matter: The difference between chatbots that explain and agents that act
  • Agent architecture: Four components (tools, agents, tasks, and teams) and how they connect
  • Build your first agent: Create a SQL tool, agent, task, and team with Oracle Select AI Agent framework
  • See it work: Ask natural language questions, get real answers from your database
  • Verify execution: Check the audit trail to see what the agent actually did
  • Familiarity with the Oracle Database and SQL is helpful but not required
  • An Oracle Login

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