Oracle Fusion Data Analytics and Risk Management Implementation Partner

Overview

Data Analytics, AI & Cloud Hosting

Denver, Colorado, United StatesPosted 2 months agoDeadline: April 6th, 2026

Fit Score

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SUMMARY

The District seeks a partner to implement Oracle Fusion analytics and risk management software for integrated data-driven decision-making and automated compliance monitoring.

KEY REQUIREMENTS

BUDGET

Estimate

$500,000 – $2,000,000

TIMELINE

RFP Issued: March 5, 2026

Questions Deadline: March 13, 2026

Addendum with Questions and Response: March 20, 2026

Proposal Submission Deadline: April 6, 2026

Evaluation of Proposals: Week of April 13, 2026

Round 2 Presentations: Week of April 20, 2026

Selection of Proposals - Intent to Award: Week of April 20, 2026

Contract Negotiation and Final Award: May, 2026

AIDP Phase 1 Implementation: June 2026 to December 2026

Risk Management Phase 1 Implementation: June 2026 to January 2027

AIDP Phase 2 Implementation: January 2027 to February 2027

QUESTION DEADLINE

March 13th, 2026

Issuing Agency

Denver Public Schools

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DESCRIPTION

The District is seeking a vendor to provide Oracle Fusion data analytics and risk management implementation partner software. The goal is to enhance data-driven decision-making through the deployment of the Oracle Fusion AI Data Platform (AIDP), which will unify analytics across Finance and HR, integrate data streams, and deliver real-time KPIs as well as predictive insights.

Oracle Risk Management/HCM Advanced Controls are key to this implementation, enabling automation of Segregation of Duties (SOD) monitoring, continuous tracking of high-risk transactions and activities, and the centralization of the internal control framework based on COSO standards. This will also involve mapping risks to mitigating controls within the Oracle Risk Management module.

The proposed solution will aggregate data from ERP, HCM, and PPM systems to monitor fiscal stewardship, workforce stability, and grant compliance at both district-wide and departmental levels.

Source attribution

This Settle analysis is based on the issuing organization’s public RFP listing.