From seed selection to supply-chain logistics — we build AI that understands the specific constraints of Indian agriculture. Every model is validated on real farm data, not just academic benchmarks.
Computer vision models identifying 40+ crop diseases from smartphone images with 94% accuracy.
Multi-modal models combining weather, soil, and satellite data for pre-harvest estimates.
Real-time pest recognition with treatment recommendations in Tamil, Hindi and English.
Optimizing logistics, demand forecasting and cold-chain for perishable produce.
Raw data rarely tells a clean story. We specialize in extracting signal from noise — through statistical rigor, time-series methods and causal inference that survive production pressures.
State-of-the-art models, engineered for the messy reality of production. CNNs for vision, transformers for language, reinforcement learning for control — all wrapped in MLOps discipline.
Object detection, segmentation, OCR and multi-camera tracking at the edge.
Fine-tuned language models, RAG systems, and multilingual speech-to-text.
End-to-end: data versioning, training orchestration, model registry, continuous retraining.
Model compression, quantization and deployment on Jetson, Coral and mobile devices.
IoT sensors + AI inference = farms that run themselves. We combine ground sensors, drone imagery and satellite feeds into a single decision engine that handles irrigation, fertilization and harvest timing.
Good research happens at the intersection of disciplines. We actively collaborate with universities, government labs, NGOs and industry partners — sharing code, datasets and credit.
Joint papers in IEEE, ACM, Springer and open-access journals.
Jointly filed patents with shared IP arrangements tailored per partner.
Select components released under permissive licenses for community use.
Co-supervised doctoral research with partner universities. 3 ongoing.
Not sure where your problem lands? Talk to us — we'll help map it to the right approach, or tell you honestly if AI isn't the answer at all.