The paperwork that never ends
Warranty claims, parts matching, invoice reconciliation, order entry. The repetitive desk work that quietly burns an hour here and an hour there — handed to software that doesn't get tired or distracted.
Applied AI · Agriculture & Operations
Software that survives a busy season.
I build AI tools for the people who run agriculture on the ground — dealerships, co-ops, retailers, growers. Things that hold up when the yard is full and the phone won't stop. Not a demo. Not a pilot. Software you'd actually keep.
Keshav Rajbux · Founder
What we do
Where I tend to start.
Wherever the day gets stuck.
Decisions hiding in your data
What to restock, when to reroute, which account is about to churn. The signals are already in your systems; I surface them where your people already work, instead of in a dashboard nobody opens twice.
Eyes on the equipment and the field
Vision and sensor models for inspecting machinery, scouting crops, and flagging conditions early — trained on the messy reality of real ag data, not a tidy benchmark.
How we work
Same way,
every time.
What's broken from the outside is rarely what's broken up close. I run the same three moves on every project because that's how the real problem shows itself.
The whole approachRide along
I learn your operation before I build anything.
I show up and watch the actual day — the bottleneck at the counter, the export someone does every Monday, the call that gets made fifteen times. You can't automate a workflow you've never seen.
Ship small, ship real
The first version runs on your real data.
No throwaway prototype to admire and then rebuild. I put a working tool in front of your team early, against your own systems, and we fix what's wrong by watching it get used.
Hand over the keys
It's yours when I leave — fully.
Your people understand how it works and why. I document it for whoever maintains it, train the ones who'll use it, and make sure the tool outlasts my involvement instead of depending on it.
Why us
Production engineering.
Ag-operations focus.
Deep applied-AI experience, learning the ag world hands-on. We lead with engineering credibility and honesty about where we are — not a brochure claim about domain expertise.
Built to run unattended
My background is production ML at Amazon scale — systems judged by whether they stay up, not whether they demo well.
Fits the stack you have
I work with your existing ERP, telematics, and spreadsheets. No rip-and-replace, no platform you're forced to adopt.
Honest about the learning curve
I'm an engineer learning agriculture, not an ag expert who learned to code. I'll tell you plainly where I'm sure and where I'm still figuring it out.
Work
No results to show yet.
Case study — first project underway
I'd rather show you a number than a slogan.
This space stays empty until the first build is in real use. When it ships, what goes here is the plain math — hours given back, mistakes caught, money that stopped leaking out.
Questions
The questions I get
before the first call.
What does Agrei build for agricultural operations?
Practical AI tools for ag dealerships, co-ops, retailers, and growers — automating warranty claims, parts matching, invoice reconciliation, and order entry; surfacing restock and churn signals from your existing data; and running computer-vision models for equipment inspection and crop scouting. Production software, not demos.
Do I need clean data or a modern tech stack to use AI?
No. I work with the systems you already have — your existing ERP, telematics, spreadsheets, and the messy real-world exports that come with them. There's no rip-and-replace and no platform you're forced to adopt.
How is this different from a big AI consulting firm?
You work directly with the engineer building the tool. I start by spending a day in your operation, ship a working tool on your real data early, and hand over something your team owns and can run without me — instead of leaving you dependent on a consultant.
How much does an AI project cost and how long does it take?
Most engagements start with a short ride-along (a week or two) to find the one or two things worth fixing first, then move in short build cycles of a couple of weeks each. Scope and price depend on what we find — the intro call is free and comes with no proposal attached.
What areas do you serve?
I work with agricultural operations across North America, remotely and on-site, with an emphasis on dealerships, co-ops, ag retailers, and the growers they serve.
Tell me where your operation hurts.
A 30-minute call, no slides. Walk me through what's slow, what's manual, what keeps breaking — and I'll tell you honestly whether AI is the right fix.
Agrei · agrei.net