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Fresco

AI-powered Division 8 (door, frame, and hardware) takeoff and estimating

Y Combinator-backed (F24) AI company whose current flagship product automates Division 8 (doors, frames, and hardware) takeoffs and estimating for commercial construction, cross-referencing door schedules, floor plans, hardware specs, and elevations to flag discrepancies before a bid goes out. The company's original 2024 product (marketed at fresco-ai.com) was a broader generative-AI documentation copilot that turned superintendents' site-walk videos and photos into reports and punch lists; that jobsite-documentation use case appears in early press coverage but is not featured on the company's current Division 8 marketing site (fresco.build).

Not publicly disclosed as a specific total. Y Combinator (F24 batch) backed; the company site also lists SignalFire, Bessemer Venture Partners, Hand Ventures, Transpose Platform, HomeTeam Ventures, and Flex Capital as investors. Tracxn categorizes the company as seed-stage. Note: some AI-generated search summaries report "$48.2M across 7 rounds" and a "$17.5M Series C" for a company called "Fresco," but this could not be corroborated by any primary source and appears to conflate this 2-person, YC-seed-stage company with a different, unrelated "Fresco" entity — treated as unverified and not used. raisedEarly Stage
Founded 2024 · 70+ companies across the US and Canada use Fresco for Division 8 takeoffs, per the company, on projects ranging from roughly 30-door tenant improvements to 4,000-door hospital renovations; the company also states 3,000+ takeoffs completed. No named customer logos or case studies are published. Y Combinator lists the team at 2 founders; Tracxn categorizes the company as seed-stage.
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WHY IT EXISTS

Why This Tool Exists

The Problem

Division 8 (doors, frames, and hardware) is widely considered the most complex takeoff in commercial construction: estimators must manually cross-reference door schedules, floor plans, hardware specifications, and elevations across hundreds of pages to catch every door and assign the correct matching hardware set. A single missed door or misread hardware group — such as an 8-foot door that needs four hinges instead of three — can erase a bid's margin, and on large projects (the company cites hospital renovations with up to 4,000 doors) the manual process can take more than a day per estimator.

The Solution

Fresco's AI reads the door schedule, floor plans, hardware specification, and elevations together, normalizes hardware sets into a structured format, cross-references them against the door schedule, and flags discrepancies (missing doors, mismatched hardware, sizing exceptions) for the estimator to resolve. The output is a validated set of hardware assignments that exports as a structured Excel file mapped to Comsense's import format, or with one click into eMullion's import wizard — carrying hardware sets, component configurations, and pricing without redundant data entry.

USAGE

How You Use It

Delivery Method
SaaSWeb App
Integrations
eMullion (one-click export into eMullion's import wizard)Comsense (structured Excel export mapped to Comsense's import format, not a direct API integration)Procore (listed on the Procore Marketplace; functional integration scope not detailed on the listing)
Disciplines
Construction, Architecture
Workflows
Data & Automation
Project Phases
Bidding/Procurement
Project Types
Commercial, Healthcare
TRANSPARENCY

Data Transparency

Exactly what this tool uses and how

Input
What it needs
Required:Door schedule, Floor plans, Hardware specification, Elevations
Optional:Existing budget or pricing data
Formats:PDF
Output
What you get
Format:Structured Division 8 takeoff with validated door and hardware assignments
Fields:Door counts and specifications, Normalized hardware set assignments, Flagged discrepancies/exceptions (missing doors, mismatched hardware), Component sizing rules (e.g., hinge count driven by door size)
Algorithm
How it works
Model:Proprietary AI the company says is "trained on millions of construction drawings" (specific model architecture/training method not published). The company's own privacy policy discloses that customer input, output, and personal data may be shared with and processed by third-party "AI Service Providers" including Anthropic, OpenAI, AWS, Google Cloud, and Microsoft Azure — suggesting the product is built on top of third-party foundation models rather than a purely from-scratch proprietary model, despite the "proprietary AI" marketing language.
Accuracy:Company claims 99% accuracy on takeoffs and a 70% reduction in estimator time versus manual takeoff. These are self-reported figures; no independent benchmark or methodology has been published.
Privacy
How your data is protected
Retention:Personal information is retained for 12 months following account termination, per the company's privacy policy. De-identified/anonymized data — including takeoff inputs and outputs — may be retained indefinitely for product improvement, AI model training, and internal benchmarking.
Training:Company privacy policy states anonymized, de-identified takeoff data may be used to improve Fresco's AI models and product performance, and in limited sales/demo contexts; raw, identifiable project data is stated not to be shared with third parties in identifiable form.
Compliance:Company states it is "SOC 2 Type 2 certified" on its marketing site and maintains a trust center (trust.fresco-ai.com); the certification report itself is not publicly available and is not referenced in the privacy policy text, No GDPR, ISO 27001, or other certification publicly disclosed
API
Integration
Endpoint:Not publicly documented — no self-serve developer API found
Method:Not publicly specified
USE CASES

Use Cases

  • ·Automating Division 8 (door, frame, and hardware) takeoffs from architectural plans and specifications
  • ·Cross-referencing door schedules, floor plans, hardware specs, and elevations to catch missed doors or mismatched hardware before bidding
  • ·Exporting validated hardware takeoffs into Comsense or eMullion for estimating and pricing
  • ·Estimating Division 8 scope on large, complex projects (from small tenant improvements up to 4,000-door hospital renovations)
  • ·Speeding up bid turnaround for general contractors and Division 8 subcontractors/distributors competing on commercial projects
PRICING

Pricing

Free
A free first takeoff is offered via "Get Your Free Takeoff" on fresco.build; no self-serve free tier for ongoing use is disclosed
Pro
Not publicly listed for the current Division 8 takeoff product — contact vendor for pricing. (Fresco's earlier, separate AI documentation copilot for superintendents was reported in 2024 press coverage at approximately $1,000/site/month with unlimited users, with discounts for multi-month or multi-site commitments; that figure predates the current Division 8 product and its accuracy today is unverified.)
Enterprise
Contact vendor for custom/enterprise pricing
Sources & Research NotesResearch date: 2026-07-16
Data Sources (11)
Fields Checked (13)
problem, solution, algorithm-approach, integrations, yearFounded, customerBase, privacy-retention, privacy-training, deliveryMethod, disciplines, projectPhases, input-formats, output-structure
Not Found (6)
fundingTotal-specific-amount, current-pricing, api-documentation, compliance-certification-report, data-hosting-location, algorithm-model-architecture
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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