autoCEQR ingests publicly available data and user-provided project inputs and returns standard analyses, data, and maps.

autoCEQR, a startup co-founded by Columbia data science alumnus Daniel Sheehan, recently joined the 2020-2021 cohort of Columbia Startup Lab, which is an accelerator that provides subsidized space and mentoring to alumni entrepreneurs to nurture their fledgling ventures.

Sheehan, who received a certificate in data science from Columbia in 2016, and Matt Sloane, an urban and environmental planner, saw the need to automate the New York City Environmental Quality Review (CEQR) process, and created software that collects, analyzes, and visualizes the data called for in CEQR reports.

autoCEQR uses data science to automate the quantitative analyses mandated by CEQR, a report that must be completed by anyone who requests a change (e.g., a rezoning, variance, etc.) from the city for a development project. In the reports, those seeking changes must assess the project’s impact on the surrounding environment, including analysis of the project’s impacts on land use, zoning, public policies, open space, the natural environment, and more.

“You can use our software to complete the report in 15 minutes, whereas doing it manually takes three weeks of consulting time at a high variable cost of about $10,000,” Sheehan said. “Our platform does the extract transform, and load processing and data reporting, reducing the time spent on the reports from weeks to minutes.”  

Earlier this year, Sheehan and Sloane presented their business plan to a panel of Data Science Institute administrators and business experts, who agreed to fund autoCEQR’s seat in the Startup Lab, which is a co-working space in Manhattan’s SoHo that has launched more than 250 Columbia-founded companies.

“Their idea is incredible,” said Daniella Raposo, director of the Columbia Startup Lab. “We are looking forward to helping them refine their business plan.”

The team is poised to turn autoCEQR into a profitable company. Both are geographic information science (GIS) professionals with non-traditional technical backgrounds. Sheehan worked as a solution engineer for a startup, as an analyst for an investment bank, and as a geographer for Columbia’s epidemiology department. Sloane has a background in planning and environmental industries.

They concede they need assistance with business planning and marketing. “We are experts in technology and in regulatory compliance, specifically in CEQR, but we have been teaching ourselves marketing and business,” Sheehan said. “Columbia’s Startup Lab has leading experts in these fields who will mentor us and help us grow autoCEQR into a mature and profitable business.”

Developers commonly hire planning consultants or real estate lawyers to do the reports, which are detailed and costly—ranging from $20,000 to $100,000 depending on the size and scope of the project. These reports typically must include 40 to 50 publicly available datasets, custom mapping, and GIS analyses of the proposed projects. Each report may take several weeks to complete, since much of the work is done manually. 

The autoCEQR team intends to market their software to real estate lawyers, planning consultants, and the city agencies that process CEQR reports. “We hope to market to all three groups and see which are the most receptive,” Sloane said. “Then we hope to license and charge per report for each client.”

Sheehan said he used techniques he learned in his DSI courses—algorithms, machine learning, exploratory data analysis, data visualization, and statistics—to create autoCEQR, and that he’s “very grateful to DSI” for subsidizing the company’s seat in the Startup Lab. 

— Robert Florida