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After 15 years in the field, I fell into software by building a health and safety app. At the same time, I had a mentor at Strabag who suggested that if I wanted to become something as a woman in construction, I needed a PhD. The company paid for it under the condition that I used the research time to analyze the company’ s data and figure out what we could do with data in construction. In doing the research, I realized how challenging it was to even access our data because it is very unstructured, siloed, and constantly changing. As such, part of my PhD was early data extraction using machine learning before AI was all the rage.
I always loved the United States and thought it was the best place to build a company, so I came to Stanford for business school in 2019. This opened up fundraising and talent doors that could only happen in the US.
When I started Trunk Tools in 2021, the goal was really to leverage advancements in AI to make construction data accessible and actionable to construction firms so they could focus on actually building rather than digging through millions of pages of documents to find answers to their questions.
What specific problems on large-scale construction projects motivated you to build Trunk Tools, and why were existing solutions falling short? The biggest problem that motivated me to start this company was the sheer amount of documentation on big construction projects. And the amount of documentation has actually increased since the field moved to email and project management systems.
For example, one of our customers was building a 400-foot tower in Manhattan that had 3.6 million pages of project documentation. If you stacked up all that paperwork, it would be three times the height of the building! Unfortunately, this is very common. It is humanly impossible to process that amount of data with a handful of project managers and superintendents. It would take a human 50 years to read through all of this. It takes AI about 30 seconds.
Before AI-native platforms like ours were available to project teams, people would spend around 20 percent of their time just looking up information. Accounting for our Q & A agent, TrunkText, alone, our customers average around 20-to-30 minutes of time savings for every question they ask the agent.
Construction teams deal with massive volumes of unstructured data. What are the biggest risks of not managing this data well? We think of unstructured data as causing two main problems:( 1) the difficulty and slow speed in accessing the information you need and( 2) the increased likelihood of discrepancies or missed details that lead to mistakes on the project.
The first of these problems tends to result in RFIs. In our own research, we’ ve found that on a typical $ 100 million project, around 1000 RFIs are submitted. These cost our customers on average about $ 3000 per RFI. Eighty percent of these are addressable by better access to unstructured data buried in their project documentation, meaning we can help them avoid up to $ 2 million in costs. In a business where GCs work off of one-to-threepercent profit margins, these savings make a big difference.
Regarding the second problem, we’ ve seen lots of opportunity to provide value to our customers in the submittal and drawing review processes. There are so many details to account for in both of these review processes, and making a mistake can easily lead to procurement delays, acceleration costs, or rework. AI has advanced so quickly and can automate most of these processes— and complete them much faster— and allow humans to do the final checks.
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