ABOUT THIS PODCAST 🔗

Update frequency:
every 19 days
Average audio length:
40 minutes
Guest interviews
English
United States
7 episodes
since June 17, 2026
episodic

LATEST EPISODE 🔗

Digital access for women farmers is not a technology gap but a trust, time, and power puzzle: field evidence shows that without women-only onboarding, familiar channels, and co-creation, most AI advisory tools remain untrusted and unused. Overlooking the realities of shared phones, limited time, an…

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Thompson Ogunsanmi is a scaling specialist at the International Institute of Tropical Agriculture, and Ifeoma Umunna is director of agriculture at DevAfric. They reveal how AkiliMo built a 700,000-farmer database across three countries with 70% of data flowing through feature phones rather than sma…
In this episode, we at AGX AI explore why localization for AI-based agricultural advisory services is not just a matter of translation or model adaptation. Audumbar Chavan, Prasaanth Balraj, and Dr. Harsh Vats of Athena Infonomics draw from implementation work with Indian state governments to show …
F1 scores weren't built for farms with cottages, livestock, and bore wells on the same parcel. Praveen Pankajakshan and Deepa Karthykeyan (Athena Infonomics) join us live for real-time Q&A and first access to new insights rethinking AI benchmarking for smallholder agriculture. Praveen explains:…
Femi Royal, Senior Advisor (governance and systems), Malcolm Durosaye, Consultant, and Ahmad Raji, Associate Consultant, are co-authors of the AGX AI discussion paper on localized Agri-LLMs for small-scale producers in Africa and India. The panel unpacks how frontier AI models fail without local cr…
AI is only as powerful as the data behind it—but what happens when that data is fragmented, incomplete, or excludes the very farmers it's meant to serve? In this episode of Grounded Intelligence, David Bergvinson is joined by Soumya Alamaru, Senior Consultant at Athena Infonomics, Jawoo Koo, Senior…
Delivering effective AI advisory services to smallholder farmers depends less on model sophistication than on building the underlying ecosystem—shared data infrastructure, consortium economics, localized digital public goods, and farmer trust—without which even the most capable AI repeats the scali…
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