Togal AI pioneered automated takeoffs from drawings—but Build Intel takes a different approach, embedding AI throughout the entire estimating workflow. We'll break down what each platform does best and help you choose the right fit for your bid process.
Togal AI claims a 98% accuracy rate on floor plans and can process drawings 10× faster than manual takeoff methods. Build Intel takes a different approach entirely: rather than fully automate drawing reading, it embeds AI throughout your entire estimating workflow—from scope validation to sub outreach to bid leveling—positioning Dexter AI as a context-aware assistant that works alongside your estimators, not in place of them. For senior estimators and preconstruction VPs choosing between these platforms, the decision hinges on whether you need a specialized takeoff tool or a comprehensive bid management system with AI woven into every step.
The construction software market has bifurcated into point solutions that excel at one task (like automated quantity extraction) and integrated platforms designed to replace multiple legacy tools. Togal AI sits firmly in the first camp; Build Intel in the second. Understanding this fundamental difference will save you months of frustration and thousands in subscription costs.
Togal AI's core value proposition is simple: upload a PDF or image of your construction drawings, and the platform automatically detects, counts, and measures building elements. The system uses computer vision trained on millions of construction documents to recognize walls, doors, windows, fixtures, electrical symbols, and other common CSI MasterFormat items. For a standard commercial office buildout, Togal AI can complete a rough takeoff in 15–30 minutes that would take an estimator 4–6 hours manually.
The platform outputs quantities organized by trade and division, which you can export to Excel, integrate with your existing estimating software (ProEst, HCSS HeavyBid, Sage Estimating), or use directly within Togal's companion costing tools. The accuracy claims—98% on floor plans—apply to well-drafted commercial drawings with clear line weights and standard symbology. Accuracy drops on hand-marked redlines, poorly scanned historical drawings, or highly custom architectural details.
Togal AI works best when your bottleneck is raw measurement time. If you're running 20–50 bids per month and spending 30+ hours per week on takeoffs, automated drawing reading delivers immediate ROI. The platform handles repetitive counting tasks—light fixtures, diffusers, doors, plumbing fixtures—with minimal oversight. You still review the output, adjust miscounts, and apply your cost database, but the grunt work is eliminated.
However, Togal AI stops at quantity extraction. Once you have your counts and measurements, you're responsible for:
Most GCs using Togal AI pair it with a manual bid management process (shared spreadsheets, Outlook folders, CRM add-ons) or integrate it into a larger platform like Procore or CoConstruct. This creates handoff friction: quantities live in Togal, sub communications live in email, bid leveling happens in Excel, and proposals are drafted in Word. You gain speed on takeoff but retain the coordination overhead that consumes 40–60% of a senior estimator's time during bid week.
Build Intel positions AI differently. Instead of fully automating one narrow task (drawing reading), the platform accelerates and validates every stage of the estimating workflow using Dexter AI—a context-aware assistant embedded across takeoff, scope generation, bid leveling, and sub outreach.
Dexter AI isn't a chatbot you query separately. It analyzes your project data in real time and surfaces actionable insights:
Build Intel's takeoffs are AI-accelerated, not fully automated. You still mark up drawings, but one-click measurements and one-click counting reduce repetitive mouse work by approximately 30%. Multi-user collaboration means two estimators can work on the same takeoff simultaneously—one handling architectural, another MEP—without file version conflicts. Custom assemblies auto-calculate material and labor from a single input (e.g., "100 LF of CMU wall" expands to block, mortar, rebar, ties, and labor hours based on your regional productivity rates).
The platform's differentiator is scope validation and sub workflow automation. Dexter analyzes completeness before bids go out, reducing costly change orders and post-bid clarifications. Automated ITB distribution with drip campaign follow-ups eliminates the 200+ manual phone calls and emails typical on a $15M+ project with 40+ subcontractors.
Togal AI's automated drawing reading is the fastest path from PDF to quantities when conditions are ideal. Upload a full set of commercial drawings (architectural, structural, MEP), and the platform processes all sheets in parallel. Within 20 minutes, you have counts for doors, windows, fixtures, outlets, diffusers, and linear measurements for walls, millwork, piping runs, and ductwork.
The system organizes results by CSI division and allows you to assign unit costs directly within the platform or export to your cost database. For a 50,000-SF office renovation with standard details, Togal AI can reduce takeoff time from 40 hours to 6 hours (including review and adjustment). The time savings compound when you're running multiple concurrent bids—processing five projects simultaneously is feasible with one estimator overseeing AI outputs instead of manually measuring each.
Accuracy depends heavily on drawing quality. The 98% claim applies to:
Accuracy degrades on:
Senior estimators report that Togal AI correctly identifies 85–95% of items on typical commercial projects but requires 10–20% adjustment time for miscounts, missed items, or incorrect classifications. For example, the AI might count a double door as two single doors, misclassify a pass-through window as a standard window, or miss recessed ceiling details that affect framing takeoff.
The platform does not validate scope completeness. If the architect forgot to dimension a bulkhead or the mechanical engineer omitted duct insulation specifications, Togal AI will process what's on the drawings without flagging the omission. You're responsible for cross-referencing specs, addenda, and RFI responses to ensure nothing is missed—the same manual validation step required with traditional takeoff methods.
Build Intel's takeoff tools are faster than manual methods but slower than Togal AI's full automation. The estimator drives the process: you open the drawing, select the measurement tool, and click start/end points. The AI acceleration comes from:
Typical takeoff time for a 50,000-SF office renovation: 25–30 hours, roughly 30% faster than manual methods and 50% slower than Togal AI's automated approach. The trade-off is precision control. You verify every measurement as you go, catching unusual conditions (sloped ceilings, non-standard door swings, concealed structural elements) that automated systems often miss.
Build Intel's unique advantage is Dexter AI's scope validation. After completing your takeoff, Dexter analyzes the quantities against:
Dexter flags gaps with specific recommendations:
"Your electrical takeoff includes device counts but no panel schedule or transformer allowance. Spec Section 26 05 00 requires contractor to provide 1,200A main switchgear. Recommend adding $40K–$60K placeholder based on similar projects."
"Architectural takeoff includes door hardware counts but no closer allowance. Spec Section 08 71 00 specifies Grade 1 closers on all exterior and stair doors (18 locations). Add $450/unit × 18 = $8,100."
This validation step catches 70–80% of scope gaps before ITBs are distributed, reducing post-bid clarifications and change order exposure. On a recent $12M healthcare renovation, a Build Intel user caught $140K in missing scope items flagged by Dexter during pre-bid review—line items the team would have eaten during construction or fought over in change order negotiations.
Dexter also drafts scope narratives for each trade package. You input your takeoff quantities, select the trade (e.g., Division 9 - Finishes), and Dexter generates a detailed scope-of-work paragraph:
"Contractor shall furnish and install all materials and labor for gypsum board assemblies per architectural drawings A3.1–A3.8 andSpec Section 09 29 00. Work includes but is not limited to: (1) 12,400 SF of 5/8" Type X gypsum board on metal studs at all rated assemblies; (2) 8,200 SF of 1/2" gypsum board on metal studs at non-rated partitions; (3) Level 4 finish at all surfaces to receive paint; Level 5 finish at surfaces to receive wallcovering per A5.2. Acoustic sealant at all rated penetrations. Contractor responsible for coordination with MEP trades for backing and blocking."
You edit and refine, but the first draft is generated in seconds. For a bid package with 12 trade divisions, scope narrative writing drops from 4–6 hours to 45 minutes.
Sub outreach is the highest-friction, lowest-value activity in preconstruction. On a typical $20M project, you invite 60–80 subcontractors across 15 trades. Each sub needs:
Manually managing this process requires 15–25 hours per project for a senior estimator or coordinator. Multiply across 10–15 concurrent bids, and sub outreach consumes 40–50% of your team's bandwidth during peak season.
Build Intel's automated sub outreach eliminates 80%+ of this work:
On a 60-sub project, Build Intel users report saving 18–22 hours of manual follow-up work. The time savings scale linearly: running five concurrent bids means you're saving 90–110 hours per month, equivalent to half an FTE.
The system also improves sub participation rates. Drip campaigns increase bid coverage by 15–25% compared to one-time email blasts, because subs are reminded at decision-critical moments (early in the week, day before deadline, morning of deadline). The platform's open/download tracking tells you who's engaged—if a sub opened the ITB three times but hasn't bid, a quick personal phone call often closes the gap.
Togal AI has no native sub outreach or bid management features. Once you complete your takeoff and apply unit costs, you export the results and handle sub coordination separately. Most GCs using Togal AI rely on:
This approach works for smaller GCs running 5–10 bids per month with established sub relationships. You know your top three electricians, plumbers, and HVAC contractors; you call them directly, and they respond reliably. The manual overhead is manageable.
But for GCs running 20+ bids per month across multiple markets, manual sub outreach becomes a bottleneck. You're juggling 500+ sub relationships, tracking 1,200+ ITB invitations per month, and spending 60+ hours per week on follow-up calls and emails. Togal AI's speed advantage on takeoff is negated by the coordination drag on the back end.
Integration with platforms like BuildingConnected or iSqFt can fill the gap, but you're now managing two or three separate tools (Togal AI for takeoff, BuildingConnected for sub outreach, Excel for bid leveling). Each handoff introduces friction, data inconsistencies, and version control issues.
Build Intel supports true real-time multi-user collaboration. Two or more estimators can work on the same project simultaneously without file locking or merge conflicts. Changes sync live across all users. Estimator A measures walls and partitions on sheet A2.1 while Estimator B counts plumbing fixtures on sheet P1.3. Both see each other's progress in real time.
This is critical for large, fast-track projects where the bid deadline is 72 hours out and the drawing set is 200+ sheets. Dividing the workload across three estimators cuts takeoff time from 60 hours to 20 hours, keeping the bid on schedule without weekend overtime.
Togal AI supports team collaboration but is optimized for single-user workflows. You upload drawings, the AI processes them, and you review the output. Multiple users can access the same project, but parallel takeoff work on different sheets requires manual coordination to avoid duplicate counts or missed items. The platform's strength is speed on individual projects, not parallelized team workflows.
Build Intel's custom assemblies auto-calculate material and labor from a single input. Example: You create an assembly called "CMU Wall - 8" Standard."
You measure once; the platform applies stored unit costs, waste factors, and labor productivity to generate a detailed cost breakdown. For repetitive elements (curtain wall, casework, ductwork), assemblies save 50–70% of the time spent on manual cost buildup.
Build Intel also auto-generates client-ready proposals from leveled bid data. Once you select subs for each trade, the platform compiles:
Proposal generation drops from 6–8 hours to 45 minutes. You review, adjust language, and send. For more on how ITB-to-proposal automation works, see our detailed breakdown.
Togal AI focuses on quantity output. Once you have counts and measurements, you export to Excel, your cost database, or estimating software to apply unit costs and build assemblies. Proposal generation happens outside the platform—typically in Word, InDesign, or a dedicated proposal tool like PandaDoc. The process works, but it requires more manual handoffs and reformatting.
Togal AI uses transparent, usage-based pricing. Plans start around $500/month for small firms processing 5–10 projects monthly, scaling to $2,000–$4,000/month for high-volume users running 50+ projects. Pricing is typically per-sheet or per-project, with volume discounts at higher tiers. No long-term contracts; month-to-month commitments are standard.
Build Intel positions itself as an all-in-one platform. Pricing typically ranges from $1,200–$3,500/month depending on user count, project volume, and feature access (takeoff, Dexter AI, sub outreach, bid leveling, proposals). The value proposition: consolidate 3–5 separate tools (takeoff software, CRM, email tracking, proposal generation, bid leveling spreadsheets) into one platform with a single monthly cost. For details, see Build Intel's pricing page.
If your primary bottleneck is takeoff speed and you already have robust systems for sub outreach, bid leveling, and proposal generation, Togal AI delivers faster ROI as a point solution. If you're managing sub workflows manually (email, spreadsheets, phone calls) and spending 40+ hours per month on coordination overhead, Build Intel's consolidated approach reduces total software spend and eliminates manual handoffs.
Togal AI's roadmap is centered on improving drawing recognition accuracy and expanding to specialty trades. Recent updates include enhanced detection for MEP systems, structural steel, and sitework. The platform is also developing integrations with major ERP systems (Sage 300 CRE, Viewpoint Vista, Foundation) to streamline cost import and export workflows. For GCs using Togal AI as a specialized takeoff layer within a larger tech stack, these integrations reduce double-entry and version control issues.
Build Intel is expanding Dexter AI's scope analysis capabilities and planning full AI-automated quantity extraction (coming soon). However, the platform currently emphasizes human-driven, AI-accelerated takeoffs to maintain quality control and estimator oversight. The roadmap includes:
AI-accelerated takeoffs, bid leveling, sub management, and proposals. Credit card required.
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