Varaha: Scaling High-Integrity Nature-Based Carbon Removals through AI-Driven Verification

Agriculture is both a major source of global emissions and one of the most effective pathways for carbon sequestration. Smallholder farmers in the Global South often lack the technical capacity to prove their environmental impact to international registries such as Verra or Puro.earth. Traditional verification systems are manual, slow, expensive, and vulnerable to fraud. Varaha addresses this gap by building a scalable digital infrastructure that converts soil health and biomass improvements into verified carbon assets, enabling farmers who practise climate-beneficial agriculture to financially benefit from their environmental stewardship.

The platform operates through a three-pillar framework: data collection, data validation, and carbon quantification. Artificial intelligence is embedded across the entire lifecycle. During pre-feasibility screening, remote sensing models scan thousands of hectares to identify disqualifying conditions such as recent deforestation or protected land status before onboarding begins. In the field, surveyors use the Varaha mobile app to submit geo-tagged photos and videos of agricultural activities. AI models immediately verify image integrity through blur detection and tamper checks while computer vision systems validate content—such as counting saplings or estimating biochar pile volume. Long-term monitoring uses time-series satellite imagery to track crop phenology and tree growth, ensuring permanence—a critical requirement for carbon credit certification.

Deployment follows a structured Golden Path workflow. Varaha partners with local organisations that manage trained surveyors responsible for mapping precise GPS polygons of each participating farm. These field boundaries are cross-verified by remote sensing teams to prevent encroachment into restricted zones and to maintain registry-grade spatial accuracy. The workflow ensures standardised onboarding, consistent data capture, and audit-ready evidence trails that meet the stringent requirements of international carbon registries.

The system has demonstrated strong validation performance across multiple geospatial tasks. Varaha's models achieve approximately 95% accuracy in building detection, 90% accuracy in waterbody detection, and 86% accuracy in tree detection across heterogeneous landscapes. These high-integrity validations enable the creation of science-backed carbon credits that command higher market value. Verified asset counts are directly linked to farmer payouts, ensuring financial returns are based on measurable environmental performance rather than promises or approximations.

By digitising carbon verification at farm scale, Varaha enables smallholders to participate in global carbon markets without bearing the cost or complexity of manual certification. The infrastructure transforms environmental stewardship into a verifiable economic asset, aligning climate goals with farmer income. The platform demonstrates how AI-driven monitoring, validation, and quantification can unlock climate finance for underserved agricultural communities while maintaining global registry standards and the scientific rigour demanded by international buyers and auditors.
For additional context and detailed documentation of this use case, please refer to pages 49 in the attached Casebook.