Tea auctions closed Week 9 broadly steady across Colombo, North India, Mombasa, and Indonesia, but dispersion inside catalogues continued to widen. Benchmark averages remain range-bound, yet price realization is increasingly determined on an invoice-by-invoice basis. Premium, well-made teas cleared competitively, particularly brighter liquoring high-grown and consistent liquidity grades, while secondary and mixed descriptions met selective demand or discounted outcomes.| Colombo: USD 4.17/kg (Week 9) | USD 4.18/kg (prior week) | North India: Prices averaged approximately USD 2.93/kg (Week 9) | USD 2.94/kg (prior week) | East Africa: Prices averaged USD 2.27/kg (Week 9) | USD 2.18/kg (prior week) | Indonesia: Prices averaged approximately USD 1.18/kg (Week 9) | USD 1.19/kg (prior week) | Podlink signup: https://pod.link/1549975153

Traceability is quickly becoming one of the defining challenges in the global tea trade.

Consumers want to know where their tea comes from, how it was produced, and whether environmental and labor standards are being met. At the same time, governments are tightening regulations, brands are facing new compliance requirements, and importers are seeking better visibility into sourcing risks. | The Tea Biz State of the Industry 2026 report describes Sustainability Compliance as the transition from voluntary sustainability claims to verifiable supply-chain data. What used to be marketing is now infrastructure. Companies are being asked not simply to say where tea comes from, but to prove it. | BIO: Samuel Lambert is a supply-chain technology entrepreneur and co-founder of ZenGate Global, developer of the Palmyra platform, a digital infrastructure designed to capture, verify, and structure agricultural supply-chain data. | Lambert’s work focuses on building traceability systems that integrate farmers, cooperatives, exporters, and brands into unified data environments to support regulatory compliance and operational decision-making. His projects span multiple commodities—including coffee, cocoa, honey, and tea—and often involve mapping farms, verifying production data, and integrating satellite, geospatial, and blockchain technologies into existing trade systems. Much of this work has taken place in emerging agricultural markets in Africa and Southeast Asia, where fragmented supply chains make reliable data capture particularly challenging. | Lambert advocates a pragmatic approach to transparency—one that strengthens existing commercial infrastructure while enabling new forms of decision intelligence built on verified supply-chain data. He is a graduate of the Australian National University, where he studied economics and design. | Podlink signup: https://pod.link/1549975153

Hormuz Crisis Threatens Global Tea Trade | Kenya Faces a Sudden Market Shock as Gulf Shipping Routes Collapse | Billions in Duties May be Returned to Importers, Including Tea Buyers | China’s Tea Exports Surge in 2025 | Green Tea Dominance Continues as Shipments Reach 419,000 Metric Tons || Podlink signup: https://pod.link/1549975153

Hormuz Crisis Threatens Global Tea Trade | Kenya Faces a Sudden Market Shock as Gulf Shipping Routes Collapse | Billions in Duties May be Returned to Importers, Including Tea Buyers | China’s Tea Exports Surge in 2025 | Green Tea Dominance Continues as Shipments Reach 419,000 Metric Tons | NEWSMAKER – Samuel Lambert, co-founder of zenGate Global

PLUS | Data Integrity at Scale

Traceability is quickly becoming one of the defining challenges in the global tea trade.

Consumers want to know where their tea comes from, how it was produced, and whether environmental and labor standards are being met. At the same time, governments are tightening regulations, brands are facing new compliance requirements, and importers are seeking better visibility into sourcing risks. Today’s guest, Samuel Lambert, co-founder of ZenGate and architect of the Palmyra supply-chain platform, works at the intersection of blockchain, geospatial verification, and agricultural supply chains. In this Spotlight conversation, we explore how structured data—from farm mapping to chain-of-custody records—can transform traceability from a compliance burden into a far more powerful form of decision intelligence for global tea markets.| Podlink signup: https://pod.link/1549975153

Tea Price Report | Episode 234 | Week 7 | Ending 13 February 2026 | Tea markets closed ISO Week 7 with a steadier tone as buyers continued to prioritize near-term cover and invoice certainty over forward risk, but showed slightly more willingness to compete when seasonal leaf and clean manufacture were evident.

Across origins, demand remained decisively quality-led: well-made teas cleared consistently, average descriptions met selective enquiry, and plainer invoices faced widening resistance, reinforcing dispersion within catalogues rather than uniform strength.

Buyer participation remained concentrated, with fewer hands setting the clearing level across several catalogues, leaving secondary lines to trade unevenly, especially where liquidity grades dominated offerings.

Exporter discipline persisted, supported by currency dynamics and elevated input costs, which limited the willingness to accept discounts and kept price floors intact even where demand for off-grades softened.

In Colombo, the early-season uplift in select high-grown and bright liquoring teas continued to anchor sentiment, while low-grown segments remained more invoice-specific and sensitive to buyer replacement alternatives.

Prices averaged USD 3.14/kg (Week 7) | USD 3.15/kg (prior week)

In North India, Assam liquidity grades continued to function as the price-setting mechanism, with buying largely contractual and execution-driven rather than speculative.

Prices averaged USD 2.01/kg (Week 7) | USD 2.02/kg (prior week)

In East Africa, competitive bidding concentrated around proven BP1/PF1 and clean dusts, while plainer lots saw wider bid-ask gaps, consistent with a market that is clearing volume but rewarding specification.

Prices averaged USD 2.22/kg (Week 7) | USD 2.21/kg (prior week)

Auction pricing in Indonesia remained secondary to contract and direct sales activity, with selective interest focused on specialty lots and improvement teas. Where spot buying did appear, it was disciplined and specification-led rather than broad-based.

Prices averaged USD 1.19/kg (Week 7) | USD 1.18/kg (prior week)

Overall, headline averages again masked the real signal: the spread between “must-own” teas and undifferentiated teas widened, and that dispersion is increasingly the durable feature of price discovery. | This week’s Tea Price Report is sponsored by the East Africa Tea Trade Association (EATTA), owners of the Mombasa Tea Auction since 1956. | Podlink signup: https://pod.link/1549975153

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

China Sets $216 Billion Tea Industry Chain Target for 2030 | India–Bangladesh Political Reset Signals Smoother Trade, Auctions and Transport for Tea | Dementia Risk Study Coverage Strengthens Tea’s Moderate-Consumption Demand Narrative

| Podlink signup: https://pod.link/1549975153

China Sets $216 Billion Tea Industry Chain Target for 2030 | India–Bangladesh Political Reset Signals Smoother Trade, Auctions and Transport for Tea | Dementia Risk Study Coverage Strengthens Tea’s Moderate-Consumption Demand Narrative

NEWSMAKER – Sein Star Kilel, CEO Co-Founder, FarmerPower.ai

PLUS | FarmerPower.ai | Seventy-eight percent of the 720,000 Kenyan smallholders who rely on tea for their livelihoods cultivate tea on plots of a half-acre or less. The sector is crucial to the economy, providing jobs for millions and contributing significantly to the country's GDP. Yet most farmers operate in the dark, receiving little to no real-time feedback on leaf quality, pricing outcomes, or how their harvest performs at factory intake. Today, we speak with Sein Star Kilel, co-founder of FarmerPower.ai, a Nairobi-based startup developing computer vision and AI tools to improve green leaf quality at the point of intake. By combining barcode traceability, conveyor-based sorting hardware, and a proprietary AI model trained to classify primary versus secondary leaf, FarmerPower.ai aims to reduce downgrading, increase premium yield, and provide real-time feedback to farmers.

If successful, the platform could reshape how quality is measured, rewarded, and monetized in Kenyan tea.| Podlink signup: https://pod.link/1549975153