Digital Investment Monitor

The AI-Powered Government Digital Investment Surveillance and Compliance Intelligence Platform is an intelligent monitoring and analytics solution designed to provide NITDA with real-time visibility into digital investments and IT projects across government institutions. The platform will leverage Artificial Intelligence (AI), data analytics, open-source intelligence (OSINT), natural language processing, and automated data collection to identify, monitor, classify and analyse government digital investments throughout their lifecycle. The platform will consolidate information from relevant government sources, procurement and project records, institutional websites, public disclosures, project documentation and other authorised data sources to create a comprehensive intelligence picture of digital investments. It will help NITDA identify emerging projects, track implementation progress, detect potential duplication or gaps, assess compliance risks, and generate actionable intelligence to support effective oversight of government IT investments and the IT Project Clearance process.

Challenge Stats

1
Teams Registered
1
Participants

Challenge Brief

Develop an AI-powered Digital Investment Surveillance and Compliance Intelligence Platform that continuously discovers, tracks and analyses government digital investments and IT projects across their lifecycle—from project conception and planning through procurement, implementation, deployment and post-implementation.

The solution should use AI, machine learning, data analytics, OSINT and automated information extraction to identify digital investment activities from authorised data sources and build a dynamic profile for each project. It should provide project intelligence dashboards showing project owners, scope, estimated investment, technology domain, implementation stage, vendors or partners where applicable, relationships with other projects, and relevant compliance requirements.

The platform should incorporate an AI-driven compliance intelligence engine capable of identifying projects that may require IT Project Clearance, monitoring available evidence of compliance, flagging potential gaps or risks, and generating alerts for appropriate NITDA review. It should support risk scoring, anomaly detection, project duplication analysis, lifecycle tracking, automated intelligence reports and predictive insights.

The system should augment—not replace—human regulatory and compliance decisions, providing NITDA officers with evidence, alerts and recommendations for investigation, verification and appropriate action. It should include explainable AI, source traceability, confidence scoring, role-based access, audit trails, data protection and secure integration with relevant NITDA systems.

Expected outcome: A proactive digital intelligence capability that enables NITDA to move from primarily reactive monitoring to continuous, data-driven surveillance and early identification of government digital investments and potential IT Project Clearance compliance risks.

Key Challenge Question

How can NITDA leverage Artificial Intelligence, data analytics, and open-source intelligence to automatically identify, monitor, track, and analyse government digital investments throughout their lifecycle while proactively detecting and supporting compliance with the IT Project Clearance process?

Goals & Mission

• End-to-end visibility of government digital investments.
• Automated detection of projects requiring IT Project Clearance.
• Proactive compliance monitoring and regulatory enforcement.
• Early identification of potential non-compliance and regulatory risks.
• Improved transparency, accountability, and digital governance across MDAs.
• Data-driven regulatory intelligence and policy decisions.
• Reduced oversight gaps, compliance

Participating Teams

Sarkinkwata
1 members

Challenge Information

Alignment: Aligned with Pillar 8: Cultivate a Vibrant Organisational Culture and an Agile Workforce in NITDA
Category: Internal Processes/ Ongoing Projects
Entity: department
Created by: Mohammed Mahmud
Created: Aug 12, 2026
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