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Tangible

AI-powered material takeoffs with live cost and carbon data for preconstruction teams

Tangible extracts quantities from Revit models and PDF drawings using an AI "Takeoff Agent," maps each element to a cost and embodied-carbon assembly, and organizes the data by trade so developers, general contractors, and consultants can compare design options and track material cost/carbon impact before value engineering locks decisions in.

$3M seed round announced May 2023, led by Foundamental and Fifty Years, with Redstone Built World Fund, Pi Labs, Asymmetric, Deco Ventures, and Suffolk Technologies participating (consistent with seed_facts: "Seed. Source: Foundamental+Suffolk"). Crunchbase and PitchBook list $7M in total funding raised to date across multiple seed tranches, with Prologis Ventures cited as a later investor; the terms of the additional ~$4M are not independently confirmed via a primary source. raisedGrowth Stage
Founded 2021 · Named customers/logos on Tangible's marketing site include Skanska (Commercial Development), Prologis, Hensel Phelps, Choice Properties, Daniels, and Wesgroup; exact total customer count not publicly disclosed
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WHY IT EXISTS

Why This Tool Exists

The Problem

Preconstruction teams manually rebuild cost and carbon estimates from static Revit models and PDF drawings, so the cost and embodied-carbon impact of a design choice is often not visible until value engineering — after major material decisions are effectively locked in.

The Solution

Users upload Revit models and PDF drawings, or sync a project directly from Autodesk Construction Cloud. An AI "Takeoff Agent" extracts quantities from the models and reconciles them against the drawings, maps each element to a cost/carbon assembly, and organizes everything by trade so teams can compare design options and export the results to Excel or a carbon report.

USAGE

How You Use It

Delivery Method
SaaS (Web App)Autodesk Construction Cloud App
Integrations
Autodesk Construction Cloud (automatic project/document sync)Excel (data export)SSO (enterprise workspaces)
Disciplines
Construction, Architecture, Sustainability
Workflows
Data & Automation
Project Phases
Preconstruction, Design Development, Construction Documentation
Project Types
Commercial, Residential, Industrial, Multifamily, Mixed-Use
TRANSPARENCY

Data Transparency

Exactly what this tool uses and how

Input
What it needs
Required:Revit models (.rvt), PDF construction drawings
Optional:Autodesk Construction Cloud project sync (auto-imports latest models/drawings), Prior project versions for design comparison
Formats:RVT (Revit), PDF
Output
What you get
Format:Structured materials/quantities data organized by trade, linked to cost and embodied-carbon metrics, exportable to Excel
Fields:Material quantities by assembly/trade, Embodied carbon per assembly, Cost data, Building performance metrics (concrete efficiency, carbon intensity, cost/ft², floor-to-floor height, slab thickness), Design-option comparisons, Outlier flags vs. portfolio benchmarks
Algorithm
How it works
Model:Proprietary "Takeoff Agent" that extracts quantities from Revit models and reconciles them against PDF drawings; Tangible's own trust documentation lists OpenAI and Anthropic as ML subprocessors, but does not name specific model versions or disclose its own model architecture
Accuracy:Not publicly specified — no vendor-published or independent extraction-accuracy benchmark found for Tangible specifically
Privacy
How your data is protected
Retention:Not publicly specified — Tangible's Trust & Security page defers to a separate Privacy Policy for retention specifics; that page returned a 404 during this research and could not be independently verified
Training:Not publicly specified — available documentation does not state whether customer project data is used to train Tangible's own extraction models
Compliance:SOC 2 Type II (Tangible states attestation is "in progress," i.e. not yet completed, as of this research), LCA methodology aligned with WBLCA guidelines, ISO 21930, and EN 15978 (environmental reporting standards, not data-security certifications)
API
Integration
Endpoint:Not publicly available — Tangible's own documentation lists API access as an "enterprise feature, coming soon"
Method:Not publicly specified
USE CASES

Use Cases

  • ·Generating AI-assisted material quantity takeoffs from Revit models and PDF drawings during preconstruction
  • ·Comparing embodied-carbon and cost tradeoffs across design options before value-engineering decisions are locked in
  • ·Tracking building performance metrics (concrete efficiency, carbon intensity, cost/ft²) across a real estate portfolio
  • ·Generating carbon reports mapped to GRESB, SBTi, Whole Life Carbon, and ILFI frameworks for ESG disclosure
  • ·Keeping takeoffs current with the latest design iteration via automatic Autodesk Construction Cloud sync
PRICING

Pricing

Free
Not publicly specified — no self-serve free tier found; the product is accessed via a login-gated web app (app.tangiblematerials.com)
Pro
Not publicly specified — no published pricing tiers found
Enterprise
Contact vendor for pricing
Sources & Research NotesResearch date: 2026-07-17
Data Sources (12)
Fields Checked (14)
problem, solution, deliveryMethod, integrations (ACC, Excel export, SSO), input-formats, output-fields, yearFounded, vendor, website, fundingTotal (seed round + lead/participating investors, consistent with seed_facts), customerBase (named logos), algorithm-approach (Takeoff Agent workflow), control-features (permissions, settings), privacy-compliance (SOC 2 status, LCA standards)
Not Found (7)
public API documentation/endpoints, AI training-data policy, specific cloud hosting region, independent extraction-accuracy benchmark, public pricing/list price, exact total customer count, full Privacy Policy detail (page returned 404 during research)
About this research: This record summarizes the cited sources and fields checked. A research date does not establish hands-on testing. Consult the original sources for current details and limitations.
ALTERNATIVES

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