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Work

A decade of building for agriculture.

Our team has built and run software for dairies, feed supply chains, farm machine data, and rural vets. Here's what those solutions were and what they taught us.

01 Solutions

What our team has built

Dairy

Dairy operations software

FeedX · 2016 – 2021

Software for running the daily operations of large dairy farms, used on farms in almost every US state.

Taken through the Techstars accelerator. It taught us, the hard way, what farmers will and won't pay for.

  • Dairy
  • Farm ops
  • SaaS

Supply chain

Animal feed marketplace

FeedX · 2016 – 2021

A marketplace for bulk animal feed, with the logistics software to move it. Feed sold into all lower 48 states.

Feed moves by the ton in semi loads, often across state lines. Most of the real work was trucking and logistics management, and we built the software to run it.

  • Marketplace
  • Logistics

Machine data

Machine-data pipeline tooling

Client work · 2025 – present

Customer-facing tools to inspect and manage data flowing in from John Deere, Case IH, and other farm machines.

Designed and built, start to finish, the product customers use to see and manage the machine-data pipelines behind a unified ag API.

  • Machine data
  • APIs
  • Frontend

AI

AI agents on farm machine data

Client work · 2025 – present

Agentic intelligence and a data lake on top of machine data, for R&D, sales, and operations teams.

Turning raw equipment telemetry into answers people can act on, without writing queries.

  • AI agents
  • Data lake

Veterinary

Voice AI for emergency vet calls

VetVoicemail · 2024

24/7 call intake that answers, takes notes, and dispatches the on-call vet.

Built for rural veterinary practices, where a missed call can mean a sick animal.

  • Voice AI
  • Veterinary

02 Case study · Farm machine data

Giving a machine-data API a product customers can see.

An established ag-data company, past product-market fit, offered one API that lets large companies pull data from John Deere, Case IH, and other machines. Customers had no way to inspect or manage their own data pipelines.

  1. Step 1

    The gap

    Customers integrated through the API alone, with no product of their own to inspect or manage the data flowing through it.

  2. Step 2

    The build

    Designed and built the customer-facing frontend for inspecting and managing machine-data pipelines, from start to finish.

  3. Step 3

    What's next

    Agentic intelligence and a data lake on top of that machine data, to power R&D, sales, and operations teams.

03 Field notes

Trials on our own farm

We've hosted and run our own technology trials on Grass Ridge Farm, including emissions-monitoring equipment at the feed bunk and hands-on methane sampling in the barn. That experience is the foundation of our field testing program.

Emissions monitoring unit at the feed bunk in a Grass Ridge Farm freestall barn
Emissions monitoring · feed bunk
Breath methane sampling on a dairy cow using a handheld analyzer
Methane sampling · freestall barn

Next step

Have something that needs to work on a real farm?

Tell us what you're building. You'll get a straight answer on whether we can help, and what it would take.