I’ve been catching up on AIMD lately and wanted to share a few takeaways after spending some time reading through their recent updates.
What they’re working on is an AI platform focused on scent. Most AI today deals with text, images, or sound. AIMD is trying to do something similar with smell by turning scent signals into structured data that AI can learn from.
From what I understand:
* AI Nose collects scent signals on an ongoing basis
* Those signals are converted into Smell ID
* A Smell Language Model (SLM) uses that data to analyze patterns over time
The setup feels very intentional. One part of the business focuses on collecting consistent data, while the intelligence layer improves as more data comes in.
On the business side, they already have a paying customer in semiconductor back-end manufacturing, and they’re working through partners that are already inside fab environments to explore broader use cases, including front-end. That kind of gradual integration usually takes time, but it’s how these environments tend to adopt new systems.
My takeaway so far is that AIMD looks like a longer-term, data-driven play that depends on execution and steady deployment rather than quick wins.
Interested to hear how others here are thinking about it.