Navi is an AI company building vertical-specific guidance platforms — starting with agriculture. Navi Leaf is our first product, built from personal conviction and lived experience of crop loss.
With AI that works offline, speaks their language, and proves its value in the first session. No special hardware. No reading required. Just point and be guided.
A world where crop loss from identifiable disease is eliminated. Where every treatment decision is data-driven, every chemical application is targeted, and every farmer has a co-pilot through the full growing season — germination to post-harvest.
Navi Leaf is built on lived experience of the problem. Growing up, I watched crop losses devastate farming families — not from bad luck, but from late detection, wrong treatment, and blanket pesticide application that drained savings without saving crops.
Navi Leaf is the product I wish existed. Built for agronomist-level accuracy, offline-first for rural India, and voice-first for farmers who should never have to look at a screen while their hands are in the field.
"Which of my 200 field workers can correctly identify late blight and apply the right fungicide? No clipboard, no paper test can answer that. Navi Leaf can — with data from every session they've ever completed."
The architecture is vertical-agnostic. Same five-agent pipeline, same SOP engine, same compliance system. Adding solar, EV, or manufacturing takes days — different domain knowledge, same infrastructure. But the first ten customers will be farms and agri-input companies. Focus wins. Breadth comes after.
₹90,000 crore ($10.8B) in annual crop losses in India alone. 150M+ agricultural workers. A $9B–$28B agri-AI market forming by 2030. The addressable problem is immense and growing.
Lived experience with crop losses, misidentified disease, and wasted pesticide spend. This is not a market analysis — it is personal conviction translated into product decisions.
PM-KISAN, Digital Agriculture Mission, PMFBY, AgriStack, e-NAM. Coordinated policy push for data-driven farming. PMFBY insurance documentation alone is an adoption driver that competitors cannot offer.
40% of Indian agricultural land has poor or no connectivity. Our offline-first architecture — on-device AI classification, on-device voice, cached SOPs, local AI models — is a structural moat Google cannot match from their cloud-only position.
Every Smart Scan, diagnostic photo, and snap verification creates labelled training data. After 12 months, hundreds of thousands of real Indian crop disease photos with treatment outcomes — impossible to replicate without years of farmer adoption.
Farmer scans a diseased crop. Instant diagnosis. Area marking. Guided treatment. Agriculture is the most universally understandable and emotionally resonant vertical in the portfolio — and the most compelling demo for investors.
Growing from $9B today. Government push, smartphone penetration, and climate pressure accelerating adoption across India and Southeast Asia.
On PlantVillage benchmark dataset. Target: >95% on real-world Indian field photos. On-device. Zero API cost. Works fully offline.
From foundation to full working demo with compliance trail, admin dashboard, and on-prem provider switch. ~$50–70 in API costs. Zero infrastructure cost.
A single configuration setting switches the entire platform between cloud-managed AI, private cloud, and local on-premise inference. All five agents — Smart Scanner, Diagnostician, Task Planner, Step Coach, Snap Verifier — are independently upgradeable and run identically across all deployment environments.
Google sells the model. Every query goes through Google's servers. A DeHaat crop protocol, a UPL treatment procedure, a government extension recommendation — none of these should be routed through Google. Navi Leaf lets the customer run everything inside their own walls, with models they control.
Request a demo and we'll walk you through Navi Leaf in the context of your operation — your crops, your protocols, your compliance requirements.