Building an AI Sales Discount Advisor with Oracle AI Data Platform

Building an AI Sales Discount Advisor with Oracle AI Data Platform

Artificial Intelligence is transforming how organizations automate business processes. Today, enterprises are building AI assistants, copilots, and intelligent agents to support decisions across sales, finance, procurement, customer service, and operations.

However, one question remains critical:

How can AI help make business decisions without violating business policies?

For decisions that affect revenue, profitability, customer relationships, or compliance, AI cannot operate without governance. Organizations still need business rules, approval processes, and complete auditability.

In this article, I demonstrate how I built an AI Sales Discount Advisor using Oracle AI Data Platform (AIDP), Oracle E-Business Suite, LangChain, Oracle Autonomous Database, and Oracle APEX. Instead of allowing an AI model to independently decide customer discounts, the solution combines business policies with AI recommendations to deliver intelligent, explainable, and governed decisions.

The principle behind the solution is simple:

Agent recommends. Policy constrains. Human approves.

The Challenge

Approving customer discounts is not as simple as offering the highest possible discount. Every pricing decision impacts revenue and profitability.

Before approving a discount, sales teams typically consider factors such as:

• Customer revenue
• Purchase history
• Gross margin
• Payment behaviour
• Outstanding balance
• Customer importance
• Existing agreements
• Company pricing policy

Traditional rule-based systems provide consistency but cannot understand business context.

On the other hand, allowing an AI model to recommend discounts without business controls creates unnecessary risk.

The ideal solution combines business rules with AI intelligence.

Why Oracle AI Data Platform?

Many AI projects become complex because they rely on multiple independent technologies such as:

• ERP
• ETL tools
• Data Lakes
• AI services
• Vector databases
• Applications
• Approval systems

Managing these platforms increases data movement, integration effort, security complexity, and governance challenges.

Oracle AI Data Platform simplifies this architecture by bringing together data engineering, AI models, governance, Spark processing, and application integration within a single platform.

This allows organizations to build enterprise AI applications while maintaining governance and reducing operational complexity.

Solution Architecture

The solution follows Oracle AI Data Platform's Medallion Architecture, where each layer has a specific responsibility.

Bronze Layer

The Bronze layer collects trusted business data from two sources:

• Live Oracle E-Business Suite customer data
• Sales discount policy maintained in Microsoft Excel

Oracle AI Data Platform accesses Oracle EBS through External Catalogs while business-owned Excel files are managed as governed catalog assets.

This keeps business data centralized while allowing business users to maintain pricing policies independently.

Business-Owned Governance

One important design decision was separating business policy from application logic.

Instead of hardcoding discount rules inside the application, the Sales team manages pricing policies using Excel.

The policy includes:

• Customer tiers
• Revenue bands
• Recommended discount ranges
• Maximum discount limits
• Approval requirements
• Negotiation guidance

When the policy is published into Oracle AI Data Platform, it becomes a governed data asset without requiring any application changes.

This allows business users to update policies quickly while developers focus on the application.

Silver Layer – Applying Business Rules

The Silver layer applies business policies before AI is involved.

Each customer is evaluated based on:

• Customer Tier
• Annual Revenue
• Gross Margin
• Order Volume
• Business Rule Priority

The system identifies the most appropriate pricing rule for every customer.

If a customer does not match any policy, the recommendation defaults to 0% discount and requires managerial approval.

At this stage, business rules have already defined the acceptable decision boundaries.

AI has not yet participated.

Gold Layer – Bringing AI into the Process

Once business policies define the permitted discount range, Generative AI provides intelligent recommendations.

Using LangChain and Oracle AI Data Platform's query_model() capability, the AI answers a focused business question:

Within the approved policy range, what is the best discount for this customer and why?

The response includes:

• Recommended discount
• Confidence score
• Business reasoning
• Potential risks
• Negotiation guidance

Instead of returning only a discount percentage, the system provides an explainable recommendation that decision-makers can understand.

Governance Always Comes First

AI provides recommendations. Business policy makes the final decision.

If the AI recommends a discount higher than the maximum allowed by policy, the application automatically limits the recommendation.

The final approved discount is always the lower of:

• AI Recommendation
• Policy Maximum

This guarantees that business policy always takes precedence over AI recommendations.

Publishing Recommendations

Validated recommendations are stored in Oracle Autonomous Database.

Each execution records:

• Customer information
• Applied business policy
• AI recommendation
• Supporting evidence
• Approval status
• Execution timestamp

This provides complete traceability for every recommendation.

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Human Approval with Oracle APEX

AI supports business decisions—it does not replace them.

Oracle APEX provides the approval interface where managers review:

• Customer details
• Applied pricing policy
• AI recommendation
• Business justification
• Risk assessment
• Negotiation guidance

Managers can approve or reject recommendations manually while maintaining a complete audit trail.

Business Benefits

The solution provides several business advantages:

• Explainable AI – Every recommendation includes clear business reasoning.
• Governed Decisions – Business policies define decision boundaries before AI execution.
• Business Ownership – Sales teams manage pricing policies without changing application code.
• Simplified Architecture – Oracle AI Data Platform brings together governance, AI, and data management within a single platform.
• Complete Auditability – Every recommendation can be traced from Oracle EBS to final approval.

Beyond Discount Management

Although this solution focuses on customer discount recommendations, the same architecture can support many enterprise use cases, including:

• Credit approvals
• Supplier onboarding
• Procurement approvals
• Warranty claims
• Insurance assessments
• Financial exception handling
• Risk scoring
• Contract review

Any business process that combines business policies with AI recommendations can benefit from this approach.

Conclusion

Generative AI is changing how enterprises make decisions. However, successful enterprise AI requires more than intelligent models.

It requires governance, transparency, and human oversight.

The AI Sales Discount Advisor demonstrates how Oracle AI Data Platform combines governed business policies, live Oracle E-Business Suite data, LangChain orchestration, and Oracle APEX into a single enterprise AI solution.

The objective is not to replace business policy with AI. It is to use AI responsibly within established business rules.

As organizations continue their Enterprise AI journey, the most successful solutions will be those that build trust alongside intelligence.

Agent recommends. Policy constrains. Human approves.