Spotlight | FarmerPower.ai

Seventy-eight percent of Kenya’s 720,000 tea smallholders cultivate half an acre or less. Tea anchors rural income, supports millions of jobs, and remains one of the country’s most important export sectors.

Yet at the farmgate, quality is largely assessed after processing—when value has already been diluted. Most growers deliver green leaf with little real-time feedback, limited visibility into downgrading, and minimal transparency into how their harvest performs once it enters the factory. Today, we spotlight Sein Star Kilel, CEO and Co-Founder of FarmerPower.ai, a Nairobi-based ag-tech startup building AI-powered intake infrastructure designed to address that structural gap.

FarmerPower.ai integrates computer vision, machine learning, and conveyor-based sorting hardware to classify green leaf at intake. Each batch is barcoded and linked to the farmer. The system evaluates measurable attributes—leaf count, moisture, size, and structural integrity—using a proprietary model that reports 93% classification accuracy. Primary and secondary leaf are separated before processing, preserving premium yield potential rather than averaging it away. The objective is economic as much as technical: reduce downgrading, increase premium yield ratios, align incentives at intake, and convert quality into measurable data.

Raised in a tea-growing family, Kilel understands the cost of information asymmetry. FarmerPower.ai is currently in prototype development and early-stage fundraising, exploring a leasing model for hardware paired with recurring software and data services.

If scalable, the platform positions itself not as a brand, but as infrastructure—shifting quality accountability upstream and reshaping how Kenyan tea is measured, priced, and monetized. |

BIO: Sein Star Kilel was raised in a family of tea growers and brings firsthand insight into the structural information gaps that affect smallholder income—particularly the absence of real-time quality measurement at intake.

She holds a postgraduate degree in AI and Machine Learning from Caltech and a master’s degree in Sustainability, Innovation, and Technology from Tomorrow University. Sayn is co-founder of FarmerPower.ai, an intake-level quality and traceability platform combining AI-driven leaf classification (93% reported accuracy), barcode-linked batch tracking, and hardware-based sorting to separate primary and secondary leaf before processing. The company is developing a factory-leasing model with recurring software services, positioning FarmerPower.ai as a scalable quality infrastructure for origin markets.

The startup is currently in prototype deployment and fundraising stages.| Podlink signup: https://pod.link/1549975153

Advertising Inquiries: https://redcircle.com/brands

Privacy & Opt-Out: https://redcircle.com/privacy