ichiwells
- Karma
- 29
- Created
- March 1, 2025 (1y ago)
- Submissions
- 0
IchiPlan.com
"The Trusted Source for Code Compliance"
Problem: The Rent is Too Damn High.
Permitting buildings and homes takes months and months across many back-and-forth cycles. The majority of time, permits are "idle"/queueing. Liability concerns prevents the government permit-issuing entities from telling residents and developers how to actually fix problems quickly and efficiently. They instead submit into the black box and a month later get another ambiguous comment.
It’s information asymmetry that both sides actually want solved.
LLMs, Computer Vision and semantic search change what's possible.
Using AI + LLMs to make permitting easier -> make homes and buildings more affordable
Hiring! https://www.ichiplan.com/join_team
LinkedIn: /jeffreyryanwells
Thank you so much for sharing this! We are using ruby to build a powerful AI toolset in the construction space, and we love how simple all of the SaaS parts are and not reinventing the wheel, but the ruby LLM SDK…
Ichi | Remote (US) | Full-Time | Senior Software Engineer, Full Stack | LLM-powered construction code compliance Ichi is building an AI-powered professional toolset to transform construction permitting and code…
One of apple’s biggest missed with “AI” in my opinion, is not building a universal search. For all the hype LLM generation gets, I think the rise of LLM-backed “semantic” embedding search does not get enough attention.…
I would actually start with the Rails Guides docs, they’re very good and running the given commands should actually work: https://guides.rubyonrails.org/getting_started.htm Just have a toy app you want to build in mind
I run engineering for a venture backed AI-first startup and we use Ruby/Rails. For us, it made sense to leverage one of the best domain modeling and ORM frameworks out there. Most of our inference is http calls to…
> Finally, building HNSW indices in Postgres is still extremely slow (even with parallel index builds), so it is difficult to experiment with index hyperparameters at scale For anyone coming across this without much…