Ever felt the drag of hours lost to manual takeoffs and document search? Togal.GPT has revolutionized construction estimating by turning complex plans into clear, actionable data. It doesn’t just spit numbers, but provides context that integrates seamlessly into your estimating process. Imagine asking, “How much drywall do we need?” and receiving a precise area calculation from Level 3, all without sifting through pages of documents. Togal’s computer vision paired with a conversational AI does just that, pulling data straight from project documents to deliver accurate measurements and summaries. This tool is not just about speed—it's about reducing costly mistakes by cutting down on manual entry and offering more collaboration with stakeholders. Companies like Coastal Construction are already reporting a significant reduction in workload and time savings. Don’t miss out on redefining your estimating processes. Full article: https://lnkd.in/evPm3b6J

𝐆𝐞𝐧𝐀𝐈 𝐂𝐨𝐩𝐢𝐥𝐨𝐭𝐬 𝐀𝐫𝐞 𝐑𝐞𝐰𝐫𝐢𝐭𝐢𝐧𝐠 𝐏𝐫𝐞-𝐂𝐨𝐧𝐬𝐭𝐫𝐮𝐜𝐭𝐢𝐨𝐧 Across the industry, new AI copilots are parsing bid documents, surfacing scope risks, and answering estimator questions in plain language. Instead of wading through hundreds of pages, teams ask, “What’s the earliest lead-time risk in MEP?” and get a sourced answer, with the relevant page excerpt. The payoff: faster takeoffs, fewer omissions, tighter contingencies. Why this matters for cost control: copilots turn unstructured content (plans, RFIs, submittals, supplier quotes) into structured signals your team can act on. They don’t replace expertise; they amplify it—flagging anomalies, normalizing line items, and proposing alternates when specifications are ambiguous. Early adopters report material time savings in bid prep, more consistent assumptions, and cleaner internal handoffs to procurement. What to watch next: copilots chaining to supplier intelligence—automatically pulling comparable SKUs, availability, and recent volatility bands so estimators see “best technical fit and likely price movement.” Expect tighter loops between estimating, procurement, and finance, with copilots logging rationales for auditability. At ProfitPlus Technologies Inc, we track these shifts because they intersect directly with prediction quality and margin protection. The north star: fewer surprises, more signal, and repeatable decisions across projects. 𝘗𝘳𝘦-𝘤𝘰𝘯𝘴𝘵𝘳𝘶𝘤𝘵𝘪𝘰𝘯 𝘵𝘦𝘢𝘮𝘴 𝘴𝘱𝘦𝘯𝘥 𝘩𝘰𝘶𝘳𝘴 𝘩𝘶𝘯𝘵𝘪𝘯𝘨 𝘥𝘢𝘵𝘢 𝘢𝘤𝘳𝘰𝘴𝘴 𝘥𝘳𝘢𝘸𝘪𝘯𝘨𝘴, 𝘴𝘱𝘦𝘤𝘴, 𝘢𝘯𝘥 𝘦𝘮𝘢𝘪𝘭𝘴. 𝘎𝘦𝘯𝘈𝘐 𝘤𝘰𝘱𝘪𝘭𝘰𝘵𝘴 𝘯𝘰𝘸 𝘥𝘰 𝘵𝘩𝘢𝘵 𝘭𝘦𝘨𝘸𝘰𝘳𝘬 𝘪𝘯 𝘮𝘪𝘯𝘶𝘵𝘦𝘴. 𝑸𝒖𝒆𝒔𝒕𝒊𝒐𝒏 𝒕𝒐 𝒓𝒆𝒂𝒅𝒆𝒓𝒔: If a copilot could cut your bid cycle time by 30% and standardize assumptions across the team, where would you redeploy those hours? #ConstructionTech #GenAI #Estimating #Preconstruction #CostManagement #AIinConstruction #DigitalTransformation #ProfitPlusTechnologiesInc

🏗️ Question for construction pros: Are you using an AI tool to compare vendor quotes? Someone in a group chat recently asked: “𝘞𝘩𝘢𝘵’𝘴 𝘵𝘩𝘦 𝘣𝘦𝘴𝘵 𝘸𝘢𝘺 𝘵𝘰 𝘤𝘰𝘯𝘴𝘪𝘴𝘵𝘦𝘯𝘵𝘭𝘺 𝘤𝘰𝘯𝘷𝘦𝘳𝘵 𝘢 𝘮𝘢𝘵𝘦𝘳𝘪𝘢𝘭 𝘭𝘪𝘴𝘵 𝘰𝘳 𝘵𝘢𝘬𝘦-𝘰𝘧𝘧 𝘴𝘩𝘦𝘦𝘵 𝘧𝘰𝘳 𝘤𝘰𝘯𝘴𝘵𝘳𝘶𝘤𝘵𝘪𝘰𝘯 𝘫𝘰𝘣𝘴, 𝘢𝘯𝘥 𝘥𝘰 𝘢𝘯 𝘪𝘵𝘦𝘮𝘪𝘻𝘦𝘥 𝘤𝘰𝘮𝘱𝘢𝘳𝘪𝘴𝘰𝘯 𝘣𝘦𝘵𝘸𝘦𝘦𝘯 𝘷𝘦𝘯𝘥𝘰𝘳 𝘣𝘪𝘥𝘴?” There are plenty of tools in the marketplace for take-offs, material lists, and cost estimating. But here’s the thing: do any of them make the quote comparison part really simple, when the quotes come in all shapes and formats (PDFs, Excel sheets, word docs, different item naming, differing units)? That leads me to my questions for you:   • What tool or workflow do you use today for comparing vendor bids side-by-side?   • If you’re not using one, what’s your current process for managing this?   • If there was a tool that could automatically ingest quotes in varying formats, normalize the line items, and present a clean comparison, how valuable would that be to you? And what would you be willing to pay (monthly or per project)? Would love to hear from estimators, procurement teams, project managers, or anyone regularly dealing with bids and material lists.

Since the inception of construction software, CFOs have relied on historical cost reports. Reporting where after-the-fact variance analysis is used to understand where a project stands is a very reactive model. For Heavy Construction, this often means learning about challenges months after the occurrence. AI can offer an alternative. ➤ https://hubs.la/Q03R4Bmv0

A few years ago, estimating was tucked away in the back office. Today, it’s where the most competitive contractors are winning work and protecting margins. As costs rise and timelines tighten, Canadian contractors are turning to AI workflows to stay ahead. Steve Watt, Director of Product for Construction and Real Estate at Sage, recently shared his insights in Canadian Contractor, highlighting how AI-powered estimating is transforming the construction industry. He breaks down the real challenges contractors face: speed, accuracy, and risk management. He also offers practical advice for those considering the move to AI-driven workflows. Read Steve’s full article here: https://lnkd.in/egm4pBfn

𝗖𝗼𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝗶𝗼𝗻 𝗱𝗲𝗹𝗮𝘆𝘀 𝗰𝗼𝘀𝘁 𝗺𝗶𝗹𝗹𝗶𝗼𝗻𝘀—𝗯𝘂𝘁 𝗔𝗜 𝗶𝘀 𝗿𝗲𝘄𝗿𝗶𝘁𝗶𝗻𝗴 𝘁𝗵𝗲 𝘀𝗰𝗵𝗲𝗱𝘂𝗹𝗲. 🏗️ In large construction projects, even a one-week delay can ripple across budgets, subcontractors, and penalties. The real challenge? Dependencies. When one task slips, everything else cascades. That’s where AI-powered scheduling steps in. Modern construction firms are now using machine learning to: ✅ Analyze historical project data to predict delay risks before they happen ✅ Optimize crew and equipment allocation to prevent idle time ✅ Simulate “what-if” scenarios to find the most efficient paths to completion One client used AI-driven scheduling to cut overruns by 30% and finish a complex project three weeks ahead of plan. Not because they worked harder—but because they worked 𝘴𝘮𝘢𝘳𝘵𝘦𝘳. If your project timelines are still managed with static Gantt charts, you’re already behind. 💡 Follow for real-world AI use cases that deliver measurable ROI—not hype. #AIUseCases #ConstructionTech #AIinConstruction #ProjectOptimization #SmartInfrastructure

AI Is Changing the Way We Build — Meet Bidking For years, pre-construction has been buried in spreadsheets, manual take-offs, and endless revisions. Aligning scopes, building estimates, and creating schedules often takes weeks — and still leaves room for error. That’s why I built Bidking — an AI-driven construction management platform built for any type of construction, from industrial and modular fabrication to commercial, civil, and infrastructure projects. Bidking doesn’t just compare bids. It reads full RFQs, scopes, and drawings, then automatically generates: ✅ Comprehensive Construction Execution Plans ✅ Manpower loading and forecasting by role and schedule ✅ Full top-down and detailed estimates with live cost modeling ✅ Primavera-ready schedules with milestones and logic ties ✅ AI-powered scope alignment and bid normalization In minutes, Bidking delivers what used to take days or weeks — giving construction leaders a consistent, data-driven foundation for every proposal and execution plan. This isn’t about replacing estimators or planners — it’s about amplifying their expertise with intelligence, structure, and speed. The same way P6 changed scheduling, Bidking is redefining estimating, scheduling, and execution planning across the entire construction industry. If you’re in construction — industrial, commercial, or civil — the future has arrived. #AI #ConstructionTechnology #Estimating #Scheduling #Innovation #ProjectManagement #Bidking #ModularFabrication #PreConstruction

Manual cost estimation is slow, static, and prone to errors. Teams spend hours calculating quantities, checking price lists, and adjusting budgets—often only after overruns occur. That approach wastes time and puts profit at risk. We help Pre-Construction & Estimating Teams make cost estimation predictive, automated, and dynamic using Machine Learning (ML). 𝗛𝗲𝗿𝗲’𝘀 𝘄𝗵𝗮𝘁 𝘄𝗲 𝗶𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁: 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗤𝘂𝗮𝗻𝘁𝗶𝘁𝘆 & 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀: ML models process project plans, drawings, and historical data to calculate material volumes, labor needs, and equipment usage—eliminating tedious manual calculations. 𝗣𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝘃𝗲 𝗖𝗼𝘀𝘁 𝗠𝗼𝗱𝗲𝗹𝗶𝗻𝗴: Our ML algorithms analyze thousands of past projects, factoring in location, market rates, complexity, and weather patterns, producing data-driven cost ranges instead of rough estimates. 𝗦𝗰𝗲𝗻𝗮𝗿𝗶𝗼 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀: Teams can test alternatives “What if we change the cladding?” with instant recalculation of total costs, including structural impact, installation time, and supplier rates. 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝘄𝗶𝘁𝗵 𝗘𝘅𝗶𝘀𝘁𝗶𝗻𝗴 𝗧𝗼𝗼𝗹𝘀: ML outputs feed directly into your project management or estimating platforms, giving estimators a live, actionable view of projected budgets. By embedding ML into your cost workflows, your team moves from reactive spreadsheets to predictive, scenario-ready decision-making—saving time, reducing errors, and improving bidding accuracy. #MachineLearning #CostEstimation #ConstructionTech #DigitalConstruction #PredictiveAnalytics #AECInnovation #ProjectManagement #SmartEstimating

🦺 Why Most Construction Projects Go Over Budget 🦺 Every contractor I’ve spoken with lately says the same thing: “We always start on budget - and end up chasing the numbers halfway through.” It’s not bad work that causes overruns - it’s poor visibility. Here’s what typically happens 👇 📉 Material costs fluctuate mid-project 📉 Change orders pile up without real-time tracking 📉 Labor hours aren’t aligned with the schedule 📉 Forecasts are static, not adaptive By the time management realizes the gap, the margin’s gone. But this is exactly where AI-driven forecasting and analytics are starting to change things. Instead of reacting to problems after they occur, companies are beginning to: ✅ Predict overruns before they happen ✅ Track bid accuracy across projects ✅ Get a live picture of labor, materials, and equipment costs It’s not about replacing estimators - it’s about giving them visibility they’ve never had before. If you’re curious to see what that looks like in action, you can try one of Aden’s free Training Agents to experience how AI learns from real construction documents. 👉 𝗧𝗿𝘆 𝘁𝗵𝗲 𝗦𝗮𝗳𝗲𝘁𝘆 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 𝗔𝗴𝗲𝗻𝘁 𝗵𝗲𝗿𝗲 https://lnkd.in/g8JyFv5R After signing up, you’ll also get access to our Analytics Agent - a tool that can transform your company’s databases or spreadsheets into a consistent, predictive analysis system. See your data come alive with trends, forecasts, and actionable insights - no coding or BI setup required. #Construction #AI #ProjectManagement #Aden #TrainingAgents #CostEstimation

I have over 32 years' experience in the construction sector across various roles. Adding to the enclosed diagram: a) Revenue recognition rules have evolved, and systems now automate tasks like invoice matching, billing, and time cards. b) AI is integrated into billing to improve accuracy with materials, labor, and travel. c) Both contractors and subcontractors use AI analytical tools.