CRISIL AI-Livestock Project: Closing a State-Level Data Gap Through Primary Coordination

Ahmar was working on an AI-led livestock evaluation project at CRISIL, covering five states across India. The project required a specific data point for one of those states, a figure that was not available on any government website or in any NABARD-published report.

Rather than flag the gap as unresolvable or work around it with a proxy, he traced the data back to its source. He identified the relevant state authority and reached out directly, eventually connecting with the Animal Husbandry Board director of that state. When that channel did not yield the data, he escalated through the CM's office, which connected him to the right person.

The ground-level data he obtained through that coordination filled the gap in the analysis and materially improved the project's output. The client noted the quality of the data, and the finding contributed to the overall credibility of the deliverable.

This project also required Ahmar to get up to speed quickly on a domain entirely outside his background. He had no prior knowledge of animal husbandry, insemination practices, or livestock economics, and had to build that understanding from scratch while running the research in parallel.