Struction

About Struction

Struction is an end-to-end takeoff quoting platform that utilizes machine learning and computer vision to analyze construction documents and generate accurate 3D-modeled quotes based on customer pricing data. This technology enables precast concrete licensors and manufacturers to streamline their quoting process, significantly reducing time and errors in project estimations.

```xml <problem> The precast concrete industry relies on manual takeoff and quoting processes, which are time-consuming, error-prone, and require specialized expertise. Inaccurate project estimations can lead to cost overruns, reduced profitability, and strained customer relationships. </problem> <solution> Struction provides an automated takeoff and quoting platform tailored for precast concrete licensors and manufacturers. The platform leverages machine learning and computer vision to analyze construction documents, extract relevant data, and generate accurate 3D-modeled quotes. By automating the takeoff process, Struction reduces the time and effort required to create project estimations, minimizes errors, and enables users to respond to customer inquiries more quickly. The platform integrates customer-specific pricing data to ensure quotes are aligned with business objectives. </solution> <features> - Automated takeoff using machine learning and computer vision to analyze construction documents - 3D modeling of precast concrete structures for accurate visualization and estimation - Integration with customer pricing data for customized quote generation - Streamlined quoting process, reducing time and errors in project estimations </features> <target_audience> The primary target audience includes precast concrete licensors and manufacturers seeking to streamline their quoting process and improve the accuracy of project estimations. </target_audience> ```

What does Struction do?

Struction is an end-to-end takeoff quoting platform that utilizes machine learning and computer vision to analyze construction documents and generate accurate 3D-modeled quotes based on customer pricing data. This technology enables precast concrete licensors and manufacturers to streamline their quoting process, significantly reducing time and errors in project estimations.

Where is Struction located?

Struction is based in Denver, United States.

When was Struction founded?

Struction was founded in 2024.

Who founded Struction?

Struction was founded by Joseph Rainey.

  • Joseph Rainey - CEO/Co-Founder
Location
Denver, United States
Founded
2024
Employees
2 employees
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Struction

Score: 72/100
AI-Generated Company Overview (experimental) – could contain errors

Executive Summary

Struction is an end-to-end takeoff quoting platform that utilizes machine learning and computer vision to analyze construction documents and generate accurate 3D-modeled quotes based on customer pricing data. This technology enables precast concrete licensors and manufacturers to streamline their quoting process, significantly reducing time and errors in project estimations.

struction.co700+
Founded 2024Denver, United States

Funding

No funding information available. Click "Fetch funding" to run a targeted funding scan.

Team (<5)

Joseph Rainey

CEO/Co-Founder

Company Description

Problem

The precast concrete industry relies on manual takeoff and quoting processes, which are time-consuming, error-prone, and require specialized expertise. Inaccurate project estimations can lead to cost overruns, reduced profitability, and strained customer relationships.

Solution

Struction provides an automated takeoff and quoting platform tailored for precast concrete licensors and manufacturers. The platform leverages machine learning and computer vision to analyze construction documents, extract relevant data, and generate accurate 3D-modeled quotes. By automating the takeoff process, Struction reduces the time and effort required to create project estimations, minimizes errors, and enables users to respond to customer inquiries more quickly. The platform integrates customer-specific pricing data to ensure quotes are aligned with business objectives.

Features

Automated takeoff using machine learning and computer vision to analyze construction documents

3D modeling of precast concrete structures for accurate visualization and estimation

Integration with customer pricing data for customized quote generation

Streamlined quoting process, reducing time and errors in project estimations

Target Audience

The primary target audience includes precast concrete licensors and manufacturers seeking to streamline their quoting process and improve the accuracy of project estimations.

Struction | StartupSeeker