The series B capital will allow the company to enhance its core product, while also adding on other workflows that focus on emissions and renewable energy. Image via combocurve.com

Houston-based ComboCurve announced today that it has raised $50 million through a series B funding round led by Dragoneer Investment Group and Bessemer Venture Partners.

Founded in 2017, the company is a cloud-based energy analytics and operating platform that uses sophisticated software to forecast and report on a company's energy assets, including renewables.

The series B capital will allow the company to enhance its core product, while also adding on other workflows that focus on emissions and renewable energy.

ComboCurve raised its series A less than six months ago, according to a release. The company was founded by Armand Paradis and Jeremy Gottlieb, who have backgrounds in engineering and finance, respectively.

“ComboCurve was created to solve critical pain points, helping energy companies better manage their forecasting, valuation, reporting and decision-making functions,” Paradis, who also serves as CEO, said in a statement. “Our solution has resulted in widespread adoption by many of the world’s leading energy companies, and this investment led by Dragoneer and Bessemer, two of the world’s leading technology investment firms, will enable us to engage with additional energy companies to operate more efficiently.”

Since the completion of the company's series A, ComboCurve has taken on more than 170 customers, including the likes of Devon Energy and Pioneer Natural Resources, according to ComboCurve's website.

The company describes its platform as a "supercharged Aries but easy to use," referring to the ARIES Petroleum Economic Software by Landmark Solutions, on LinkedIn. The platform provides forecast modules, workflows and fully integrated economics, with GHC and carbon reporting features in the works that will allow users to estimate future emissions.

“ComboCurve is in the early innings of building a truly enduring franchise that is rapidly becoming the software backbone of their customers’ day-to-day operations,” Christian Jensen, partner at Dragoneer Investment Group, said in a statement. “We are excited to partner with Armand and his world-class team as they continue to deepen their suite with existing customers and expand their platform into renewables, emissions reporting, and all corners of the energy market.”

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Houston food giant Sysco to acquire competitor in $29 billion deal

Mergers & Acquisitions

Sysco, the nation's largest food distributor, will acquire supplier Restaurant Depot in a deal worth more than $29 billion.

The acquisition would create a closer link between Sysco and its customers that right now turn to Restaurant Depot for supplies needed quickly in an industry segment known as “cash-and-carry wholesale.”

Sysco, based in Houston, serves more than 700,000 restaurants, hospitals, schools, and hotels, supplying them with everything from butter and eggs to napkins. Those goods are typically acquired ahead of time based on how much traffic that restaurants typically see.

Restaurant Depot offers memberships to mom-and-pop restaurants and other businesses, giving them access to warehouses stocked with supplies for when they run short of what they've purchased from suppliers like Sysco.

It is a fast growing and high-margin segment that will likely mean thousands of restaurants will rely increasingly on Sysco for day-to-day needs.

Restaurant Depot shareholders will receive $21.6 billion in cash and 91.5 million Sysco shares. Based on Sysco’s closing share price of $81.80 as of March 27, 2026, the deal has an enterprise value of about $29.1 billion.

Restaurant Depot was founded in Brooklyn in 1976. The family-run business then known as Jetro Restaurant Depot, has become the nation's largest cash-and-carry wholesaler.

The boards of both companies have approved the acquisition, but it would still need regulatory approval.

Shares of Sysco Corp. tumbled 13% Monday to $71.26, an initial decline some industry analysts expected given the cost of the deal.

Houston researcher builds radar to make self-driving cars safer

eyes on the road

A Rice University researcher is giving autonomous vehicles an “extra set of eyes.”

Current autonomous vehicles (AVs) can have an incomplete view of their surroundings, and challenges like pedestrian movement, low-light conditions and adverse weather only compound these visibility limitations.

Kun Woo Cho, a postdoctoral researcher in the lab of Rice professor of electrical and computer engineering Ashutosh Sabharwal, has developed EyeDAR to help address such issues and enhance the vehicles’ sensing accuracy. Her research was supported in part by the National Science Foundation.

The EyeDAR is an orange-sized, low-power, millimeter-wave radar that could be placed at streetlights and intersections. Its design was inspired by that of the human eye. Researchers envision that the low-cost sensors could help ensure that AVs always pick up on emergent obstacles, even when the vehicles are not within proper range for their onboard sensors and when visibility is limited.

“Current automotive sensor systems like cameras and lidar struggle with poor visibility such as you would encounter due to rain or fog or in low-lighting conditions,” Cho said in a news release. “Radar, on the other hand, operates reliably in all weather and lighting conditions and can even see through obstacles.”

Signals from a typical radar system scatter when they encounter an obstacle. Some of the signal is reflected back to the source, but most of it is often lost. In the case of AVs, this means that "pedestrians emerging from behind large vehicles, cars creeping forward at intersections or cyclists approaching at odd angles can easily go unnoticed," according to Rice.

EyeDAR, however, works to capture lost radar reflections, determine their direction and report them back to the AV in a sequence of 0s and 1s.

“Like blinking Morse code,” Cho added. “EyeDAR is a talking sensor⎯it is a first instance of integrating radar sensing and communication functionality in a single design.”

After testing, EyeDAR was able to resolve target directions 200 times faster than conventional radar designs.

While EyeDAR currently targets risks associated with AVs, particularly in high-traffic urban areas, researchers also believe the technology behind it could complement artificial intelligence efforts and be integrated into robots, drones and wearable platforms.

“EyeDAR is an example of what I like to call ‘analog computing,’” Cho added in the release. “Over the past two decades, people have been focusing on the digital and software side of computation, and the analog, hardware side has been lagging behind. I want to explore this overlooked analog design space.”