Building Fusion Extensions with Redwood + AI Agents: A Smart Step Forward
Oracle’s Redwood UX brought a new wave of design consistency and user delight to Fusion Applications. Now, with the rise of AI Agents in Oracle Cloud, we’re entering the next phase: smart extensions that are not just reactive, but proactive.
In this post, let’s explore how to combine Redwood-based Visual Builder apps with Fusion AI Agents to create intelligent, personalized, and impactful extensions — the kind that don’t just respond, but guide users.
Why Combine Redwood UX with AI Agents?
Modern enterprise users expect more than just pretty interfaces — they want smarter workflows, relevant insights, and less clicking. When you blend Redwood’s modern design system with AI Agents’ intelligence capabilities, you unlock:
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Dynamic recommendations
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Proactive nudges and alerts
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Intelligent data lookups
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Personalized guidance
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Faster decision-making
In short, you deliver extensions that think for the user, not just wait for input.
How It Works: The Smart Extension Model
Here’s the architecture at a high level:
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Redwood App built in Oracle Visual Builder
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Connects to Fusion’s REST APIs to read/write business data
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Integrated with AI Agent Studio or prebuilt Oracle AI models
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Optionally leverages Oracle Integration Cloud (OIC) for orchestrating multi-step flows
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Embedded directly in Fusion (via Page Composer) or launched as a standalone app
This stack lets you deliver intelligent capabilities while staying fully within the Oracle ecosystem — no bolt-ons required.
Real-World Use Cases
1. Smart Project Costing Tracker
A Redwood app shows project spend vs. budget. AI Agent highlights overspending trends and suggests actions like freezing PO releases or reassigning tasks — all in real-time.
2. Guided Onboarding for Suppliers
AI Agent helps fill out forms, validates GST/VAT data, and nudges users to upload required documents based on country-specific rules. The Redwood UI ensures clarity and accessibility across roles.
3. Proactive Leave Planning Assistant (HCM)
Redwood extension suggests ideal leave windows based on team availability and auto-checks policy compliance. AI-driven logic helps reduce manual back-and-forth.
4. AI-Powered Invoice Exception Handler (Finance)
Invoices stuck due to mismatches are flagged by the agent. The Redwood app guides the AP user through resolution — pulling in supplier contact, prior approvals, and risk scoring.
How to Build One: Key Steps
1. Define the Use Case and Outcome
Focus on what you want to improve or predict. Is it faster decision-making, automated classification, or guided user actions?
2. Build the Redwood UI
Use Oracle Visual Builder:
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Redwood Web App template
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Connect Fusion data via REST APIs
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Ensure it’s responsive and user-role-aware
3. Integrate the AI Agent
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Use AI Agent Studio to design an agent (intent, rules, models)
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Connect it to relevant Fusion datasets
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Decide whether to embed the agent in the UI or trigger it behind-the-scenes
4. Connect the Dots
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Combine the Redwood UI with real-time outputs from the AI Agent
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Use toast messages, guided steps, or side panels to display agent feedback
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Optional: Use OIC for orchestration if multiple apps/systems are involved
5. Embed & Test
Deploy the Redwood app and embed it into Fusion (via Page Composer or Navigation link). Simulate real user scenarios to test:
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Agent accuracy
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UI responsiveness
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Business rule alignment
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Role-based visibility
Tips for Success
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Start small — one agent, one outcome, one page
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Work closely with business users to define realistic agent behaviors
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Use Redwood design tokens and layouts for consistency
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Monitor performance, especially when calling models or APIs in real-time
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Ensure proper error handling and fallback options
Summary
Combining Redwood UX with AI Agents moves us from automation to augmentation. You’re not just building tools — you’re building assistants that help users work smarter.
With Oracle’s roadmap focused on embedded intelligence and conversational UI, your Redwood extensions can now become part of an AI-powered Fusion experience that’s proactive, human, and scalable. ✔
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