FBR introduces AI-based chick counting system to monitor poultry sector

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Islamabad, January 27, 2026 – In a move to tighten oversight of the poultry industry, the Federal Board of Revenue (FBR) has announced plans to implement an advanced Artificial Intelligence (AI) system to monitor every chick produced across Pakistan’s hatcheries.

The initiative aims to curb revenue leakages and ensure accurate reporting in the poultry sector.

Official documents reveal that the FBR is inviting bids from technology vendors to supply and install production monitoring systems at key points in poultry operations. The system will track day-old chicks (DOCs), including broiler chicks, layer chicks, and those produced through integrated breeder-hatchery operations. Using AI-powered vision analytics, IoT-enabled incubation monitoring, and other validated technologies, the system will capture, process, and transmit real-time production data to centralized computing units for accurate record-keeping.

Vendors will also integrate these systems with FBR’s database, allowing authorities to reconcile hatchery output by chick type, production batch, or cycle. To ensure accuracy and reliability, bidders must demonstrate a live proof-of-concept at operational hatcheries, showing the system’s performance in high-humidity, temperature-controlled, and bio-secure environments.

The project covers nationwide poultry facilities, including egg storage, setter and hatcher rooms, chick processing and grading lines, packing, and dispatch areas. Participating vendors will provide ongoing technical support, periodic updates, and maintenance to guarantee system efficiency and compatibility with FBR regulations.

The procurement will follow the Public Procurement Regulatory Authority (PPRA) guidelines through a two-stage bidding procedure, with pricing proposals aligned strictly to FBR’s specifications. The AI-based initiative is expected to enhance transparency and accountability across Pakistan’s poultry sector, marking a significant step toward digitized monitoring of agricultural production.