Launch HN: Bild AI (YC W25) – Understands Construction Blueprints Using AI
Roop and Puneet's Bild AI automates construction material estimation using specialized machine learning models, addressing inefficiencies costing the industry $30 billion annually, while seeking feedback from construction professionals for improvement.
Roop and Puneet, founders of Bild AI, are developing a machine learning platform that automates the extraction of material quantities and cost estimates from construction blueprints. The current manual process is labor-intensive and error-prone, costing the construction industry approximately $30 billion annually. Puneet's experience in building homes in Canada highlighted the inefficiencies of traditional takeoff methods. Bild AI employs a suite of specialized machine learning models for specific tasks, such as detecting floor areas and counting framing elements, rather than relying on a single end-to-end model. This approach mirrors techniques used in self-driving car technology, focusing on accuracy through dedicated models. The company is currently collaborating with early customers, including flooring suppliers, to enhance their estimating workflows and aims to expand its services across various trades. The founders are seeking feedback from the Hacker News community, particularly from professionals in the construction industry, to better understand their workflows and challenges. They invite interested parties to upload blueprints for evaluation and discussion of potential use cases.
- Bild AI automates material quantity and cost estimation from construction blueprints using machine learning.
- The manual process currently costs the construction industry around $30 billion annually due to inefficiencies.
- The company uses specialized models for specific tasks to improve accuracy in blueprint comprehension.
- Bild AI is working with early customers and aims to expand its services across multiple trades.
- The founders are seeking feedback and collaboration from industry professionals to refine their approach.
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- Many commenters express excitement about the potential to reduce inefficiencies in the construction industry.
- There are questions regarding the accuracy of cost estimations and the sources of material pricing data.
- Some users suggest integrating the tool with BIM software for better efficiency.
- Concerns are raised about the slow adoption of new technologies in the construction sector.
- Several commenters emphasize the importance of user feedback and collaboration with industry professionals for further development.
Coincidentally, yesterday I had a client meeting and they ask for exactly that. I'm working as lead developer for https://howie.systems and we are building a co-pilot (knowledge platform) for the AEC industry.
Would love to have a talk. Your product could save us lot's of work!
- You’re right, data is very hard to come by. I’m curious, how do you plan to get around this? Outsourcing human labeling? We found it to be a very difficult task.
- The subcontractors and local construction companies we talked to were overwhelming excited about the idea.
- It’s entire people’s jobs to get this done and done correctly. They sit on site holding the pdfs in their hands, manually counting and calculating. You bet a lot of mistakes occur. They would absolutely love to have a digital assistant for this.
- Some of them (especially managers and owners) are quite technical and are using software such as BlueBeam and other CAD software to make these calculations. It’s quite manual currently, but gives great insight into a better solution. This led us to having the user manually select the symbol they wanted counted (which ML struggled to get right). Just getting the part counts (and highlighting them in the pdf) was a huge help!
- Impressive you got square footage calculations correct! In our experience, there was way too much variation between architects (and multistep dimension labeling) which made it hard (even for humans) to get right. How has your model generalized OOD thus far?
- Are you planning to integrate voice? Many of the subcontractors we worked with are very low tech. They usually talk with their clients in person, on the phone, or maybe text. But they don’t use email or their smart phones for much.
I will be following your work! I have friends who would love to use this once it passes the human threshold.
I'm asking because even though I am (mostly) technically illiterate I have asked both ChatGPT and Claude to help me build a scraper for construction material costs, from the suppliers we use, that can be updated in realtime or at least monthly. Haven't done anything with those instructions yet, but I would love nothing more than to use a tool that we could feed a blueprint into and then would tell me, with "laser-focus accuracy" <smile> how many x's the project would need and the costs. Even better yet if it could compare costs from suppliers and guide us to the lowest-cost supplier.
Edit: oh, while you're thinking of replying, how high fidelity do the blueprints need to be? Again, I'm sure you specify somewhere, but too lazy to find it. How far along the spectrum from "drawn on a napkin" to "fully standardized" do you accept?
The benefit of estimating quantities and cost cycles in with pre-con and business development, the artifacts during the pre-con design phase tend to be different than the takeoff artifacts which are often transformed through BIM.
Did you learn something to the contrary? Or are you purposely targeting smaller firms and projects that don't use Bim and maybe won't for a long time?
On the other side, architects are using Revit more and more and takeoffs like square footage of flooring are accurate and take no time at all. That's another industry slow to change and that used to take more effort so many architects aren't providing that information to their clients, but technically there's nothing preventing it. There's a bit more hand waving when it comes to calculating number of studs etc, but that is pretty straightforward as well.
Source: I'm funemployed as a drafter for a local architect after 25 years in software.
If owners/developers understood this they could create contract structures that incentivize more fluid data collaboration aka the quantity take offs automatically generate as you are designing.
Pragmatically though in the current AEC landscape there is still a need for 2D QTO, nice work
It looks like your launch is opening this up to the general public - why not niche down to GCs? Maybe the launch is focused on simply gathering more blueprint data to feed your models?
Estimators miss things ALL THE TIME. It's the subject of seemingly endless in-house arguments between PMs and Estimators:)
One thing I've been thinking about is if you could use a model like this as the first pass for permitters (Like a GitHub Actions CI/CD) who review blueprints.
Many developers use the regulatory side of various engineering approval processes as a quality control check which costs money and time for the regulator who is tasked with enforcing a standard.
It would also be good to speed up the workflow for developers saying hey, this thing looks weird did you really mean to do this?
And then further on, you could add a way to check it for constructability. My framer friends often get annoyed at whatever engineer because the way the structure is designed is materially inefficient or hard to construct.
What's crazy about this is that the AI revolution is going nuts. We've started with Steel and customers who would traditionally bid on paper are now jumping straight to AI takeoffs. The impact is real.
One customer recently told us that he was able to bid on $200M more than he would have been able to otherwise: https://www.linkedin.com/feed/update/urn:li:activity:7300899.... That's a couple of million in revenue that they would have worked away from because of capacity constraints.
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