Togal.AI

Cloud takeoff software that auto-detects rooms, walls, and counts from uploaded drawings, then lets an estimator edit, classify, and export quantities.

Why a $5–10M GC would pay

A mid-size GC usually has one estimator (or a very small precon desk) and still has to produce takeoffs on every bid. Hours spent tracing floor plates and counting doors are hours not spent checking specs, calling trades, or sending another bid. Togal’s pitch is that AI does the first pass on architectural plans so the estimator reviews instead of clicking every polygon. Published customer pages describe lean precon teams using it that way: Stevens Construction (four estimators, healthcare / industrial / data-center work) runs takeoff in Togal and pushes quantities into Ediphi; T. A. Loving’s preconstruction manager describes pulling many walls at once and unchecking the ones that do not belong; UrbanCore says conceptual estimates that used to take a week or more now happen in hours. Those firms are larger than a $5–10M GC, but the job is the same — more bids, fewer missed rooms, without hiring another estimator.

What it actually does

Upload a plan set. Togal auto-names sheets from title blocks, can auto-detect scale (the estimator still has to confirm it), and runs in the browser so more than one person can work the same takeoff. The green Togal Button is the AI first pass: detect, measure, count, and label spaces and features. Search tools find a symbol, a text tag, or a hatch pattern across the set. Manual tools (split, cut, merge, arc) exist to fix the AI. Drawing-set compare overlays revisions. A 3D viewer (vendor blogs and 2026 release notes) renders the 2D takeoff so heights and surfaces are easier to spot-check. Togal.CHAT answers questions from uploaded plans and specs and can draft RFIs, submittal lists, and proposals. Quantities export to Excel or PDF, or into a connected estimating tool. Assemblies exist at least for drywall (materials / labor / equipment as you measure). Togal says it is SOC 2 Type II compliant. Sign-up on the pricing page is “Try Now” plus a demo on your own drawings.

A University of Kansas paper that Togal republishes (work dated March 2025) is the only independent accuracy write-up on their site: first-time user, architectural floor plans, Togal vs On-Screen Takeoff. Across the fire-station and hotel cases, Togal plus manual cleanup was about 70–76% faster; after adjustments, most quantities sat within 5% of OST. The same paper says do not bid the raw AI: it misses projections, eats annotation lines as walls, mixes doors and windows, and does not read legends or notes. On a messy scanned set and on a structural foundation plan, AI was weak or limited. On an RCP, AI did not split ceiling types, so most of the work was still manual.

The homepage also claims “up to 98% accuracy on floor plans” and “5x faster.” Those are vendor slogans. They do not publish the test set or method. Prefer the KU paper.

Fit

For a US GC at $5–10M that bids commercial, multifamily, or similar work from PDF architectural plans and already lives in Excel for pricing. Also sold to trade estimators (drywall, electrical, mechanical, plumbing, glazing, landscaping, painting, FF&E) and to GCs coordinating those trades. Homepage testimonials include small outfits (painting, flooring, lumber), so this is not an enterprise-only SKU.

Not the right first buy if takeoff is not your bottleneck, if most of your work is civil / site / structural / elevation-heavy (AI is built for architectural floor plans; other sheets are mostly manual plus search), if you need a full cost database and bid-day package in one product, or if you only do residential flips with napkin quantities. A $5–10M GC that already has Bluebeam for markup still needs Bluebeam; Togal is takeoff, not a PM or PDF studio.

Pricing (public)

Published on https://www.togal.ai/pricing (checked 2026-08-23):

Growth: $299 per user per month, billed yearly. Unlimited automated takeoffs, chat prompts, and image/symbol searches. Internal collaboration for users on the account; unlimited external collaborators who do not need their own Togal seat.
Business: custom quote, listed for teams with 4+ users. Adds onboarding/training, a dedicated support rep, classification library template, quantity discounts, security compliance, and SSO.

Major credit cards. Multi-license discounts and “enterprise solutions” are sales conversations (sales@togal.ai). Cancel by contacting them before the next renewal. They do not publish a month-to-month Growth price. A separate marketing page (apply.togal.ai) advertises a 14-day free trial; the main pricing page routes new users through demo / “Try Now.” Treat trial length as something to confirm on the current signup flow.

Integrations

Only what Togal (or a partner press page they host) states:

Excel and PDF export of quantities (features page; export grouping/filters described in their evaluation blog).
Ediphi native integration: Togal quantities map into Ediphi’s unit-price catalog; estimators accept or defer updates. Stevens Construction is the named first live customer (case study, press).
Zebel used with Togal by UrbanCore Construction for conceptual pricing (case study).

Not listed as current first-party integrations on the live marketing site: Procore, Autodesk Construction Cloud / Autodesk Takeoff, Bluebeam, PlanSwift. Older third-party articles mention a Procore Marketplace listing; Togal’s current site does not document it. Do not assume drawings sync from Procore or Autodesk.

Watch-outs

Human QA is required. KU: raw AI is a starting point; bid only after an estimator walks the sheets. Scale must be checked per drawing.
Plan types. Strongest on clean architectural floor plans (rooms, walls, doors, some fixtures). Elevations, MEP, structural, civil/site: expect manual takeoff plus search, not one-button AI. Poor scans and busy annotations degrade results.
It is not your estimating system. Pricing, assemblies beyond what you configure, and bid forms still live in Excel, Ediphi, or whatever you already use.
Accuracy slogans. Use “98% / 5x” as marketing. The published independent result is “faster, then within ~5% of OST after review,” on a small architectural sample, one user, March 2025 software.
Lock-in. Cloud app, annual seats. Exports exist, so you can leave with a spreadsheet; the AI classifications and chat history do not travel. External guests can view/collaborate without buying seats, which helps subs.
Price vs headcount. One Growth seat is about $3,600/year. For a $5–10M GC that is a real line item. It only pays if the estimator actually sends more complete bids.

Compared with

STACK — Cloud takeoff plus a broader estimating / bid-management suite; less of a one-button AI first pass, more of an all-in-one precon desk.
Autodesk Takeoff — Lives inside Autodesk Construction Cloud; the comparison that matters if your jobs already have usable models, not just PDFs.
Kreo / Beam — Other AI-from-PDF takeoff tools a GC would demo in the same week; pick by how they handle your plan quality, not by homepage percentages.
PlanSwift (and On-Screen Takeoff) — Desktop click-and-count. Cheaper muscle memory for some estimators; no cloud collaboration story like Togal’s, and the KU paper is explicitly Togal vs OST.

Verdict

Yes — a $5–10M US GC should try it this quarter if they bid from PDF architectural sets and takeoff time is why they skip jobs or send thin numbers. Book the “use our drawings” demo, run one recent commercial or multifamily set, and time the AI pass plus your own cleanup against how you do it in Bluebeam, PlanSwift, or Excel today. Buy a Growth seat only if that test shows hours back and you still have a human checking every sheet. Skip it this quarter if your work is mostly site/civil, model-based Autodesk takeoff, or you needed Procore/Autodesk sync (not documented on their site now). Do not replace an estimator with it; the published research says the opposite.