{"id":101234,"title":"Rudus: AI-powered takeoff for concrete subcontractors","tagline":"Rudus helps concrete contractors produce quotes 80% faster","body":"**TL;DR:** Rudus is an AI-powered takeoff and estimation platform built for concrete subcontractors. Takeoff is the process of measuring and quantifying materials from concrete plan sheets. Rudus identifies every concrete structure (footings, walls, columns, slabs), pulls in related details, and eliminates hours of manual quantity calculation.\n\n**Ask:** If you know anyone in construction, we would greatly appreciate a warm introduction. Concrete-specific would be even more amazing. We would also love to talk to anyone who has built computer vision models.\n\n**Launch video**\\\n\u0026lt;\u003chttps://youtu.be/QdXKLNN4IQo\u003e \u0026gt;\n\n**The problem:**\n\nConcrete subcontractors are the backbone of every building, and their estimating workflow hasn't changed in 20 years . A senior estimator opens a PDF, manually traces every footing and grade beam, then hand-builds an Excel spreadsheet with 300+ line items- volumes, formwork, rebar by bar size with lap splices and development lengths. One bid takes 20 to 40 hours. Most firms have just a few estimators. That means they physically cannot bid on most of the work available to them. \n\nThe software incumbent in this trade hasn’t been updated since 2020. Past that, every AI takeoff tool on the market was built for GCs and treats concrete as one checkbox. None of them expand rebar assemblies. None of them compute development lengths. None of them output quantities the way a concrete estimator actually prices work. We built Rudus for this trade and only this trade. \n\n**Solution**\n\nAn estimator uploads their structural PDFs. Rudus auto-classifies every sheet (foundation plans, section details, footing schedules, frame elevations) and routes each to the right processing pipeline. Computer vision detects concrete elements across the drawing set and follows cross-references across sheets to resolve dimensions and detailing, catching elements that plan-only tools always miss. Each element gets expanded into full assembly line items: concrete, formwork, and rebar with all the calcs an estimator would normally do by hand. A typical foundation package goes from a handful of assemblies to 80-120 priced line items. The estimator reviews, overrides where needed, and exports straight into their existing workflow. We cut takeoff time by 80% and help estimators bid 3-5× more projects without adding headcount. From plan upload to bid package, every part of the workflow gets faster. \n\n**How we got here**\n\nSahil and I were engineers at Amazon and Airbnb respectively. We are both from Cupertino, CA and have been best friends since high school, always talking of starting a company together. Sahil took a construction management class and realized estimation workflows hadn't changed in decades. We started cold calling, walking into offices, showing up at job sites, and everyone told us the same thing: slow estimation is the biggest bottleneck in their business, but every new product they've tried has failed. We quickly realized that the reason those tools failed is a lack of trust. Estimators stake million to billion dollar bids on these numbers, and they won't trade their workflow for a black box. We took a different approach: software that accelerates their current workflows rather than replacing it by forward deploying our product into their current estimation workflow. The response from the industry was overwhelmingly positive, and we now ship weekly to estimators with decades of experience. They keep asking for more.","slug":"QKo-rudus-ai-powered-takeoff-for-concrete-subcontractors","created_at":"2026-05-12T02:44:19.484Z","updated_at":"2026-05-25T01:56:47.023Z","total_vote_count":69,"url":"https://www.ycombinator.com/launches/QKo-rudus-ai-powered-takeoff-for-concrete-subcontractors","share_image_url":"//bookface-static.ycombinator.com/assets/ycdc/yc-og-image-c440a0ad1dacfb86eeeb343717479cc54d256614449b4ef719977a0a451f8bc8.png","company":{"id":31346,"name":"Rudus","slug":"rudus","url":"http://rudus.ai/","logo":"https://bookface-images.s3.amazonaws.com/small_logos/407f4a93871730524968180bcf20dd23fc9ce7b2.png","batch":"Spring 2026","industry":"Real Estate and Construction","tags":["Artificial Intelligence","SaaS","Construction","B2B"],"search_path":"https://bookface.ycombinator.com/company/31346"}}