● Blog · 5 notes

Notes from the field

What we learn putting models into real processes — written for the people who have to make them pay back

Latest · Delivery ·

Why AI pilots stall — and how to get them to production

A successful demo is not a successful pilot, and a successful pilot is not a product. Five things that separate AI projects that reach production from the ones that stay on a slide.

Read the note →

Voice AI that gets through: lessons from calling farmers

Some audiences don't answer email or fill in forms — they pick up the phone. What we learned building a voice AI robot that holds natural conversations with farmers and hands organizers only the leads that matter.

Voice AI4 min read

From engineering PDFs to a live catalog with an LLM

How we use language models to turn hundreds of pages of technical documentation into a structured product catalog — and why engineers stay in the loop for every description.

LLM · Data4 min read

Computer vision on the cameras you already have

You rarely need new hardware to put computer vision into a working process. What ordinary CCTV and phone cameras can do, where they fall short, and how to design the alerts people will actually read.

Computer vision4 min read

Where AI actually pays back: a checklist before you start

Most AI projects that disappoint were chosen badly, not built badly. A seven-question checklist for picking a process where a model returns its cost in 6–12 months.

Strategy5 min read

Contact

Tell us about a process that's expensive to do by hand

We'll tell you whether there's work here for a model and what it takes to put numbers on it. The first conversation comes without a sales pitch

Send a request →