The AI company building the next generation of AgriTech products.
AGRIVISION AI is an AI-first technology company focused on designing and building intelligent agriculture products and digital ecosystems.
We combine artificial intelligence, analytics, predictive systems, automation, and modern software engineering to solve agriculture challenges at scale.
- 2026AGRIVISION AI founded
A founder-led, AI-first AgriTech company set out to build intelligent agriculture products.
- NowYieldAI Global is live
AI crop advice, live government market prices, weather, and scheme guidance — live in the USA, India, and Canada.
- NextGrow & expand
Scaling YieldAI Global toward 40+ countries with deeper crop intelligence.
- RoadmapPlanned modules
AgriSense (IoT), deeper yield prediction, and smart irrigation — planned for future implementation.
Our mission, vision & the app that proves it.
AGRIVISION AI exists to close the gap between modern AI and the people who grow the world’s food. Here is what we stand for — and the live product where it becomes real.
Intelligence every farmer can trust
To put accurate, AI-powered agricultural guidance in the hands of every farmer and extension worker — grounded in real data and delivered in their own language. Good advice should not depend on where you farm, how big your holding is, or which language you speak.
- Answers grounded in real government and agronomic data, not guesswork
- Every response in the farmer’s own language
- Honest about uncertainty — routes to a local extension officer when it matters
A smarter harvest, everywhere
A world where every farming decision — in every language, in every country — is backed by intelligence farmers can rely on. We start with the extension workers and smallholders who feed the world, and scale outward from there.
- From 3 countries today toward 40+ over time
- Built for the ~1,200 households one extension worker often serves
- Voice-first and multilingual by design
AI for a sustainable future
Technology in service of the land, the farmer, and the next harvest. We build tools that are honest about what they know — and careful with what they don’t — because a confident wrong answer can cost someone an entire season.
- Right over impressive, every time
- Less waste: smarter inputs, water, and pesticide use
- Building in public, honestly
YieldAI Global
Our live AI farming assistant, and the clearest expression of everything above. A farmer asks a real question — about a crop, today’s market price, the weather, or a government scheme — and gets a clear, correct answer in their own language. Available in India, the USA & Canada, with a free trial.
Founder-led, built with conviction.
Vijesh Reddy Golamari
Vijesh Reddy Golamari is the sole founder of AGRIVISION AI (Agrivisionai Inc), headquartered in Detroit, Michigan, and a Generative AI Engineer and Technical Lead at Symplore Inc. He founded AGRIVISION AI to bring AI-first product thinking to global agriculture, and leads product, AI, and platform engineering — building intelligent agriculture products, including the flagship platform YieldAI Global, from the ground up.
“Agriculture is the largest industry in the world — and the most under-served by modern software. We’re here to change that, one intelligent product at a time.”
Bhanu Prakash
Turns farmer feedback and product data into insights that shape YieldAI Global — what works, what breaks, what ships next.
Bala Sleeva Thirumala Reddy
Drives business strategy — market positioning, partnerships, and the path from live product to real adoption.
Grow more.
Use less.
Most wasted input comes from a decision made on a calendar or a habit rather than on a signal. YieldAI Global exists to put a signal behind those decisions — so a farmer sprays, waters and feeds when the crop actually needs it.
Spray on a forecast signal instead of a fixed calendar.
Catch disease early from a photo and treat the affected plot, not the whole field.
Schedule watering against evapotranspiration and the forecast, not habit.
Apply against what the soil actually lacks rather than a default dose.
We haven’t measured the aggregate effect across farms yet, so we don’t publish a percentage. When we have field data worth standing behind, we’ll publish the result and the method behind it.