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Optibus, a Fast-Growing Transit Optimization Startup, Raises $12 Million Series A Round

The company uses machine learning to suggest the most efficient use of resources. But it wants to offer more.

Optibus took just three years to create artificial intelligence-powered software that optimizes transit operations and sign clients in 200 cities on multiple continents. It’s grown fast, and now the company has $12 million it wants to use to build up its product.

The Series A round, which follows a $1 million seed round in 2015, will also support sales and marketing growth, but as it announced the round the company emphasized product development.

Right now, the company’s focus is on providing software that offers transit agencies real-time situational awareness as well as optimization suggestions for things like routes, timing and asset management. For example, Optibus might be able to help decide where to locate bus depots or use one vehicle where two might have operated before. Chief Executive Officer and co-founder Amos Haggiag said that might help an agency run all its services, with no routing or scheduling changes, using 190 vehicles instead of 200. It could also offer scenarios for different schedules and routes.

The company’s mantra is moving its customer agencies from a static paradigm to a dynamic one, where data can constantly provide paths to the most efficient way of running a system.

“It’s not something you run once, it’s basically all the time optimizing the system,” Haggiag said.

For a company whose product is already founded in the cloud and machine learning — two cutting-edge technologies, especially for the public sector — it’s hard to tell what more product development might look like. A press release from the company says that it plans on creating “an integrated citywide operating system” for all types of transportation that will predict passenger demand, though Haggiag said he could not offer more specific details.

But his vision of the future is ambitious. In so many words, Haggiag thinks public transportation agencies can bring people back from personal vehicle use — and now, ride-sharing — to mass transportation.

“To do that you have to create a new type of transportation that doesn’t exist today,” Haggiag said.

He did specify that Optibus isn’t looking to get into the on-demand transit game, where some agencies are looking to follow the lead of ride-sharing services like Uber and Lyft by sending vehicles out to pick up riders where they are instead of at fixed stops. Rather, Haggiag said, he wants to build on the existing world of public transport and make it more dynamic, more efficient, more data-driven and overall better for riders.

Machine learning algorithms like the ones Optibus uses have come into vogue in recent years, offering transportation agencies a slew of new ideas for how they might catch up with, and then keep ahead of, their challenges. Much in the way science uses modeling to find the likeliest scenarios in a given event, machine learning can use historical data to automatically identify what a change in a system might mean for the rest of the system. And because it is automated, it can use massive quantities of data to identify correlations and patterns where humans might not think to look.

In transit and transportation, that could mean a lot of things. It could mean assessing how much time a piece of physical infrastructure has left before it will need to be replaced. It could help predict traffic congestion and even accidents. It could help urban planners and traffic engineers better understand how the different projects they’re considering would impact transportation, or simply figure out which projects are most urgently needed.

It’s a fast-growing field, and Optibus has managed to grow faster than most. Haggiag attributed that to the way the company structured its product and business strategy. The product was built for quick integration and implementation in days or weeks. And the nature of optimization means that the company’s business case tends to be better the larger an agency is — the same percentage of savings applied to a larger pool of expenditures is a bigger deal.

And Optibus has, in fact, signed some very big clients — in the U.S., they include agencies in Los Angeles, Washington, D.C., and Austin, Texas.

“We are trying to offer our clients, which are the transit agencies and operators, a much more dynamic service that will be able to take them into the next generation of transportation,” Haggiag said.

The Series A round was led by Israeli venture capital firm Pitango, with participation from Verizon Ventures and Sir Ronald Cohen.

Editor's note: This article has been corrected to distinguish that Optibus has clients in 200 cities and not necessarily 200 clients.

Ben Miller is the associate editor of data and business for Government Technology. His reporting experience includes breaking news, business, community features and technical subjects. He holds a Bachelor’s degree in journalism from the Reynolds School of Journalism at the University of Nevada, Reno, and lives in Sacramento, Calif.