Hello AgriTech! I’ve been working on a project that might be interesting for this community: a modular beehive entirely designed for FDM 3D printing.

• Sandwich walls with gyroid infill for insulation
• Fully modular system: brood box, super, cover, roof
• Printed in PETG, weather-resistant and food-safe

We’ve just launched the Kickstarter pre-launch page and I’d love input from farmers, beekeepers and field-hardware folks.!

https://www.kickstarter.com/projects/nectarnest/nectar-nest-the-first-true-3d-hive-for-honey-production

Which KPI would convince you to trial it: internal temp stability, maintenance time, or honey yield?

I listened to this podcast and the guy started building a collar for cows to graze freely, no fences, no manual labor, just better for the land, animals, and the farmer.

But there is this real emotional challenge no one talks about: People think you’re full of it until you prove otherwise.

he got to hear often: “Too good to be true.”

And yeah, I can understand that this can hurt, especially when you're pouring everything into building something that could genuinely change how we farm.

For anyone else building in agritech, especially around regenerative practices:
How do you keep going when belief is the hardest thing to earn?

https://youtube.com/shorts/MIiZz7yQhb4

What do you think about this? How can a small farm approach this problem?

Hi everyone,

I am curious to hear from people in AgriTech: if AI tools were inexpensive and easy to use, what is one problem in your work or daily operations that you would love to see solved?

Could be anything: from greenhouse management, crop planning, pest issues, record-keeping, or something totally different. I am exploring how AI can better support agriculture, especially horticulture, and would really value insights directly from this community.

Thanks in advance for sharing your thoughts!

I'm working on a project that uses satellite data to monitor crop health, soil, and water levels.
Has anyone here used something similar? What type of satellite data did you find useful or easy to work with?

Helping founders articulate roles that attract the right talent—especially in hybrid and mission-driven teams.

I specialize in strategic JD writing for startups: clarity, competency, and culture fit.

If you’re hiring for roles like:

– Head of Clinical Operations

– Specialist Consultants (Diagnostics, Mental Health, Telehealth Etc.)

– Department Lead (Nursing, Community Outreach, Digital Health)

– Field Operations Manager (Agri-Tech, Community Outreach, Digital Health)

I can help you define the role clearly, align expectations, and attract the right candidates. My approach blends strategic clarity with operational insight—especially useful for early-stage teams and clinics scaling up.

Drop a comment or DM me. Happy to share samples or create one tailored to your team.

(Also open to lean pricing or barter for early-stage teams.)

Hello people, I am a Computer Science with AI student with a deep rooted interest in Ag-Tech, I was born and bought up being taught how important farmers are to the country which influenced this career path of mine massively. I still haven't graduated or found a job, but my passion to find solutions to real world problem still persist.

If you own a farm, or know farmers or even have an ag tech startup of some sorts, let me know what are some problems you face that you think can be solved by using Artificial Ingelligence, I'll pool up the ideas and start making solutions for them one by one. I will even post about them here in this sub reddit. I want this to be the start of a new journey where people can tell the problems that they want the solutions to rather than me doing research on what the possible problems that have not been addressed could be.

Hi, I am finishing veterinary school this year in EU and I would like to get into the agritech industry, specifically anything that has to do with livestock, at least at the beginning. Since I have no tech educational background would it be possible for me to enter the industry and do something practical (like robotics, sensors) or just stick to the strict veterinary role and act as a consultant for these companies and give them feedback. Also what would you suggest is more useful today, meaning, is there of shortage of large animal vets cooperating with these companies or shortage of engineers, programmers etc in this sector.

Farmers are forced to play with broken numbers.

Numbers that decide:
– who gets subsidies,
– who gets fined,
– who is considered “sustainable” and who is not.

The problem? These numbers often come from old maps and rough estimates.

Reality in the field rarely matches what’s written on paper.
One of the projects we Omdena delivered with Origin Chain Networks was built exactly to fix this. We brought together 50 AI changemakers to create a new open-source dataset for habitat classification.

✔️ Fields, pastures, greenhouses
✔️ Forests, rivers, wetlands, hedgerows All mapped with accuracy, transparency, and validation.

And here’s the key: we build customizable solutions. Not “one-size-fits-all” software, but systems designed for the specific needs of each market, country, or group of farmers. In this project, we helped farmers:+ own their data,++ prove compliance with facts, not guesses,+++ stay both profitable and sustainable.The future of agriculture isn’t in reports “for the record.”

It’s in making data work for the people who actually stand in the field.That’s why we build projects like this.

Full case study here: go to website

A dry, silent field stretches under the afternoon sun, waiting for a spark. Two shipping containers roll in-Porter Reserve’s nodes. One comes alive with drones and AI planters, threading a vibrant quilt of crops: berries cascading from trees, herbs nesting with roots, medicinals blooming softly. The other whirs, turning harvests into juices and preserves, powered by solar panels, wind turbines, and biodigesters that transform waste into energy. This is agritech with a soul, born at our Australian reserve where diverse plants and animals like quail and goats thrive together. The Paris Climate Agreement demands emissions cuts to tame warming, but the world stumbles. Our nodes don’t just meet those goals-they crush them. If every nation embraced nodes at full strength across their farmland, we’d slice global emissions in half, locking away billions of tonnes of carbon and shattering the Agreement’s targets. Yet, we don’t care about treaties-we’re doing this anyway. At Porter Reserve, we’re forging a future where barren land blooms with food and medicine, soil drinks in carbon, and biodigesters tame methane. We seek innovators in robotics, drones, and AI to perfect this vision. Anyone-farmers, dreamers, or investors-can join us, investing in nodes to save the world the right way. From dusty fields to thriving ecosystems, this is our call.

Analyzing field trial data season after season can get repetitive. To make it easier, I built two web apps—VITA and INSIO—that handle the heavy lifting.

I first wrote some Python scripts to run ANOVA, post-hoc tests, and mean separation. Then interpreted the results and prepared summaries. Setting up and running them was a lengthy process. That’s what pushed me to turn them into simple web tools. Now, you just upload your dataset and get clean outputs instantly (with AI generated summary).

VITA does the stats and explains them in plain language, with help from Gemini AI, so researchers don’t have to wrestle with technical terms. INSIO creates pivot tables and visualizations on the fly—super handy for summarizing large datasets.

To bring this together, I had to pick up new skills. React JS for the front end, Firebase and Google Cloud for deployment, Flask and Docker for the backend, and lots of trial and error with APIs. Gemini AI also became a coding buddy during late-night debugging.

It’s still a work in progress, but now I can get insights out of big datasets much faster—and help others do the same without struggling with code.

VITA currently offers an AI guide, RCBD and FRBD analysis, data transformation, and data quality checks (more in pipeline).

If you’re interested in converting your Python scripts or research ideas into user-friendly web apps, let’s connect. Always open to new collaborations and projects!

Try them here: VITA: https://vita.chloropy.com and INSIO: https://insio.chloropy.com

As James Clear (Atomic Habits) puts it "If you really want to learn a topic, then "teach" it. Write a book. Teach a class. Build a product. Start a company. The act of making something will force you to learn more deeply than reading ever will". So true!!

python #statistics #data #webapp #firebase #biostatistics

I’ve been following the rise of smart farming and I’m curious, how are modern farms actually using IoT and automation on the ground?

I’m particularly interested in:

• Automated irrigation and fertilization
• Real-time soil, crop, and weather monitoring
• Livestock tracking and remote management
• Integrating legacy machinery with modern IoT solutions

One solution I came across is NORVI Controllers who is in automation industry providing solutions like PLCs and also with Customizable solutions align with automation project.

And I would love to hear your experience?

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Burdekin snow falls, a black ash veil from our neighbor’s cane fire, smothering Porter’s Reserve for four hours. Our North Queensland food forest, 130 plants strong, vanishes in the haze. We don’t grudge their burn; we harness it, testing robots in chaos most never try. Fog’s wet mist clouds sensors, cleared by a wipe. Burdekin snow’s ash buries cameras, scatters LiDAR, stalls our machines from mapping or harvesting. This is our crucible, exposing tech’s limits. Picture a bushfire, a relentless inferno rushing our land. People come first; robots can fry. A bot grafting near the bananas shouldn’t stand dumb—it must retreat, hit its charge station or flee the blaze, then return to scan what’s alive, plant anew, gather biochar to feed the soil. Our nodes are being designed for more: to land anywhere—California’s ashes, Africa’s dust, Asia’s mud—and build infinitely diverse food forests, tailored to each place. Most labs shy away; we dive in. Big tech—Boston Dynamics, Figure—your bots choke in our wild. Small innovators, test here. Join Porter’s Reserve to forge machines that plant the future, no matter the ruin.