This tender invites qualified firms to undertake the AI-based digital transformation of the Benazir Bhutto Shaheed Human Resource Research & Development Board in Karachi, Sindh. The project falls under the IT Software & Licenses category and is issued by the Board under the Universities & Boards Department, Government of Sindh. The scope covers end-to-end digitization including workflow analysis, system design, development, customization, deployment, testing, and commissioning of an integrated digital management system. Key modules include HR, training, finance, procurement, monitoring, coordination, e-filing, and reporting dashboards. The system must be cloud-based, AI-powered, and scalable with features like predictive analytics, anomaly detection, and smart automation. Hosting services with unlimited bandwidth within Pakistan are also required. The project demands robust data security, compliance with government standards, and post-deployment support including training and maintenance. Bidders must be registered with EPADS and tax authorities, possess at least five years of relevant experience, and demonstrate ISO/IEC 27001 or equivalent certification. The firm should have completed ERP/MIS/digitization projects including government assignments. Compliance with PEC categories and FBR/ATL status is essential. The bid security is 2% of the bid amount, and performance security is 5%. The contract will be awarded based on technical and financial evaluation under Sindh Procurement Rules 2010 (amended). Submission deadline is **25th March 2026 at 12:00 PM**, with bid opening at 12:30 PM the same day. Bids must be submitted online via the SPPRA EPAD system. The physical address for correspondence is Deputy Director (Procurement), 5th Floor Statelife Building #3, Dr. Ziauddin Ahmed Road, Karachi. Pro-Tip: Ensure your bid includes all required certifications and original bid security documents before the deadline. Missing or incomplete documentation is a common cause for disqualification. Also, carefully review the technical evaluation criteria to maximize scoring potential.