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ML Systems
Take your house apart, rebuild it larger from its own parts
Most teardowns end in a landfill. ML Systems models your home, runs a reverse takeoff of what is actually in it, and lets lenders bid to fund the rebuild. Deconstruct instead of demolish, then rebuild larger from the recovered material.
I believed AI and Machine Learning was moving too fast for the human consciousness so I LLC'ed ML Systems.
I now am attempting to rebuild the American Dream of homeownership by rebuilding the existing homes.
I run a construction company in Rhode Island, and I built this because the industry has a hole in it.
There is software for buying a home, selling it, renovating it, insuring it and financing it. There is almost nothing for the moment a house comes down, which is exactly when most of its material value gets destroyed. A machine flattens the structure, and old-growth framing, brick, fixtures and hardware go to a landfill. Rhode Island's Central Landfill is projected to hit capacity around 2046.
So the app starts there. You enter an address, it builds a model of the house, and it runs a reverse takeoff: what is actually in this structure, and what is it worth. From there it tracks the whole loop in one place - financing through deconstruction, design and construction - with one auditable record per home.
Two things I want to be straight about, because I would rather you trust the numbers than be impressed by them.
The software is shipped and real. The construction loop is modeled and has not been run yet. I am about to run the first cycle on my own property. Every claim in our public repo is labeled MEASURED, MODELED or ASPIRATIONAL for exactly that reason.
The concepts are all open at github.com/MLSystemsRI/ml-systems-public - the ledger design, the ontology, how we compress a house into a canonical model. Happy to go deep on any of it.
About ML Systems on Product Hunt
“Take your house apart, rebuild it larger from its own parts”
ML Systems was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #157 on the daily leaderboard. Most teardowns end in a landfill. ML Systems models your home, runs a reverse takeoff of what is actually in it, and lets lenders bid to fund the rebuild. Deconstruct instead of demolish, then rebuild larger from the recovered material.
On the analytics side, ML Systems competes within Android, iOS, Artificial Intelligence and Climate Tech — topics that collectively have 659.5k followers on Product Hunt. The dashboard above tracks how ML Systems performed against the three products that launched closest to it on the same day.
Who hunted ML Systems?
ML Systems was hunted by Salman Parvez. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of ML Systems including community comment highlights and product details, visit the product overview.
Salman Parvez