Dear Lord Why?​

Because I hate knowing that the car dealership is screwing me, AND I have buying constraints on acceptable models / controls. Rather than build the dealer API integration myself, after some complaining on Reddit, I stumbled upon Visor.vin (built by Colin and the team, reachable at brothers@visor.vin).

Was there a happy ending?​

Yes. I'm scheduled to take possession of a Toyota Grand Highlander 2026 Hybrid Nightshade in November.

2026 Toyota Grand Highlander Hybrid Nightshade Edition (Midnight Black Metallic)

AI has assisted the detailed write-up (and, fittingly, the negotiation). Thanks to Colin and the Visor.vin team for the inventory API, and to kenn-io for the original msgvault.

Due to competing priorities, getting the first "baby" model out the door on ExecuTorch took far longer than anticipated.

What does the model do?​

The model monitors a webcam powered by Thingino and served to HomeKit via Scrypted. It produces two primary predictions published to MQTT, which are then exported to HomeKit via Homebridge using mqtt-things:

• Door Open/Closed
• Car Home/Away

I have probably bit off more than I can chew with this project. However, the progress made on automated labeling and model conversion has been a game-changer for my local-first AI experiments.

With Scrypted / Thingino up and stable, the next goal is to replace my janky garage door sensor with a camera-based sensor. With some luck, I can extend this to every camera in the house cheaper and more accurately than Frigate, but let's not get ahead of ourselves.

The monetization strategy for private AI in the home is still in its infancy. Do we monetize the orchestration server for private re-training? Or is the value in the "Private Models" themselves? Alternatively, perhaps a data-privacy-first exchange allows for anonymized datasets to be contributed back to the collective in exchange for lower hardware overhead.

A continuation of the previous blog post.