Togal

What is Togal?

Togal.AI is an advanced pre-construction AI program aimed at streamlining the estimation process for construction projects. It utilizes automation, machine learning, and AI to automatically detect, measure, compare, and label features and spaces in architectural plans. This technology enhances efficiency in the construction industry by providing accurate estimations, reducing manual errors, and saving valuable time for construction estimators, architects, and contractors.

One key benefit of Togal.AI is its high level of accuracy in detecting, measuring, and comparing features and spaces in architectural plans. By leveraging machine learning algorithms, Togal.AI ensures precision and reliability, significantly reducing the margin of error compared to manual processes.

Testimonials from users highlight the time-saving and efficiency-boosting aspects of Togal.AI, with features such as quick collaboration, cloud-based analysis, instant drawing analysis, and automated processes. Users praise the software for speeding up processes, improving accuracy, and facilitating collaboration among team members in construction estimation and planning tasks.

Overall, Togal.AI stands out in the industry as a cutting-edge technology that revolutionizes the pre-construction phase by offering advanced automation, accurate estimations, and collaborative features tailored for construction estimators and industry professionals.

Who created Togal?

Togal was created by Patrick Mc Gowan, the CEO of the company. Togal was launched on April 15, 2021, with a focus on revolutionizing the construction industry by providing innovative software for estimators. The company's aim is to offer advanced construction estimating tools that automate the takeoff process, improve efficiency, and streamline the pre-construction phase. Togal.AI has been well received in the industry, with users praising its ability to reduce manual mistakes, save time, enhance productivity, and provide precise estimates thanks to its AI algorithms.

What is Togal used for?

• Automatically detect and measure project spaces and features on architectural plans
• Compare drawing sets and quantify changes with a simple click
• Collaborate in the cloud with multiple team members working on the same takeoff in real-time
• Instantly analyze any drawing regardless of file type
• Eliminate manual tasks with AI-powered technology
• Enhance efficiency by speeding up processes
• Contribute to time savings by automating the takeoff process
• Improve accuracy in floor plan measurements
• Facilitate collaboration among trade contractors by providing pre-done takeoffs
• Contribute to swift decision-making through quick extrapolation of information from architectural drawings

Who is Togal for?

• Construction estimators
• Architects
• Contractors

How to use Togal?

To use Togal.AI effectively, follow these steps:

1. Sign Up and Consent: Create an account on the Togal.AI platform and consent to the use of cookies for optimal functioning.

2. Data Sharing: Agree to specific data sharing policies to enable Togal.AI to perform key functions like detecting, measuring, and comparing features and spaces in architectural plans.

3. Understanding Construction Documents: Utilize Togal.AI to understand construction documents accurately. It automates the detection, comparison, and measurement of spaces and features, reducing manual errors and saving time.

4. Architectural Analysis: Architects can use Togal.AI to analyze construction documents, detect, measure, label, and compare features and spaces across various designs, aiding in decision-making.

5. Contractor Benefits: Contractors benefit from Togal.AI in the pre-construction phase by refining the understanding of construction documents and providing automated solutions for accurate estimations and efficient project planning.

6. Accuracy and Efficiency: Togal.AI provides a high level of accuracy in measuring and comparing features, minimizing mistakes in construction estimates. It enhances understanding through machine learning algorithms, improving decision-making efficiency.