3 Houston tech innovators to know this week

Who's who

Tech startups are popping up across industries from real estate to oil and gas, and these three founders are among the leaders in technology. Courtesy images

Often, technology and innovation are mistaken for each other. While not mutually exclusive, both tech and innovation work well together in Houston across all industries — from oil and gas to real estate and social media. These three founders engaged technology for their individual startups.

Srini Katta, founder and CEO of Social Chains

Courtesy of Social Chains

As a social media user, your data is already out there and being used for marketing purposes. But, rather than the Facebooks or Googles of the world making a profit, Srini Katta wanted to create a platform where users made a profit off their own data.

"On our platform, the user is a stakeholder. Our platform distributes 50 percent of the profits to the users," he says.

Social Chains already has 5,000 users and, Katta says, that's with little to no marketing efforts, which Katta is about to launch.

Martin Kay, founder and CEO of Entera Technology

Courtesy of Entera

Martin Kay, who splits his time between Houston and the Bay Area for his startup Entera Technologies, knew there had to be a better way for people searching for a home to buy. He drew a comparison between homebuyers and Netflix viewers to create Entera's software.

"We're a little bit like Netflix," he says. "They go out and get content from everyone, and they begin to watch your behavior. So, Netflix has 2,000 profiles and you probably fit five or six of those. We have almost 100 profiles and what we do is say, we're going to understand what you want, watch your behavior and instead of giving you 40,000 properties on a big map, we actually match you based on your preferences, to the five or six houses that are best for you."

Houston-based Entera has grown as the platform loads more and more data for its users to engage with.

Luther Birdzell, CEO and founder of OAG Analytics

Courtesy of OAG Analytics

Luther Birdzell always knew he wanted to run his own company, but the software and analytics professional worked in various industries before realizing that oil and gas had a huge opportunity for savings using analytics. He founded OAG Analytics in 2013 to help provide a solution for these companies.

"When I founded OAG Analytics, our mission then — and still is today — was to build a platform for the upstream oil and gas industry that enables them to manage their data, introduces world-class machine learning in minutes without having to write a single line of code, and allow them to run simulations on the resulting analysis," Birdzell says.

The company has grown to 25 employees and tripled its revenue last year. The team is forecasting another year of high grow for 2019.

This Houston company has the key to a more exact searching process when it comes to finding a new home to buy. Courtesy photo

Tech company uses machine learning to buy homes in Houston

game changer

For most consumers, the home buying process includes a very specific online search. People specify their neighborhood requirements, the number of bedrooms or bathrooms, backyard size, and more — yet still, the search results in a staggering amount of homes. It's way more than anyone can reasonably look at.

That's where Martin Kay and Entera Technology, the company he founded and is CEO of, come in. Kay, a 20-year veteran of the tech sector, who's bought multiple homes as rental properties, realized the way to solve the problem of that kind of search engine overload was through machine learning. He now works with some of the largest home-buying companies in the world, helping them find properties that match the specifications they have to attract the clients they want.

"All residential real estate is a consumer product," he says. "Ultimately, the people who are going to live in that home care most about, is it a nice home with a big backyard neat good schools, is it safe? The [home buying] companies are trying to figure out what do the end consumers really care about so we can give them exactly what they need?"

To do so, Entera collects data — lots and lots of it. Kay and his team have taught their software programs what a chef's kitchen is, for example. They did so by compiling tens of thousands of photos of kitchens and telling the software, "This is a kitchen." Then, they taught it to recognize what makes a chef's kitchen — a larger size, more than one sink, high-end appliances. They used the same techniques in identifying things like millennial-friendly neighborhoods or neighborhoods that were up-and-coming on the real estate scene. They draw from listings available with the Houston Association of Realtors and beyond, a vast array of tens of thousands of homes.

Officially launched in 2017, Entera blends its data collection and analysis with on-the-ground service. After Entera's proprietary software collects what it thinks home-buying companies want, members of Entera's service team go out to look at the homes.

While Entera has been working with larger home-buying companies — like firms that buy tens of thousands of homes every year — Kay says they have begun working with smaller entities, and he figures within the next few years, Entera will be using the same data collection and machine learning to work with individual home buyers.

Based in Houston, Entera has operations in New York and San Francisco as well. The company has 17 full-time employees, along with approximately 100 contractors in its markets. And while Kay understand a human touch is needed in business, he loves that he can use a data model to present unbiased opinions to his clients.

"[Real estate] actually affects people's lives meaningfully," Kay says. "Real estate data — where you live, what your neighborhood is, how you make that choice — …this data matters to people in a way they can tangibly touch and understand and feel. We can help people make what are big, complex choices that are often highly ambiguous. I love it because it matters. You can measure how it matters immediately."

Data-driven tech

Courtesy of Entera

Entera focuses on collecting data and analysis and pairs it with on-the-ground service. After Entera's proprietary software collects what it thinks home-buying companies want, members of Entera's service team go out to look at the homes.

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Rice University researchers unveil new model that could sharpen MRI scans

MRI innovation

Researchers at Rice University, in collaboration with Oak Ridge National Laboratory, have developed a new model that could lead to sharper imaging and safer diagnostics using magnetic resonance imaging, or MRI.

In a study recently published in The Journal of Chemical Physics, the team of researchers showed how they used the Fokker-Planck equation to better understand how water molecules respond to contrast agents in a process known as “relaxation.” Previous models only approximated how water molecules relaxed around contrasting agents. However, through this new model, known as the NMR eigenmodes framework, the research team has uncovered the “full physical equations” to explain the process.

“The concept is similar to how a musical chord consists of many notes,” Thiago Pinheiro, the study’s first author, a Rice doctoral graduate in chemical and biomolecular engineering and postdoctoral researcher in the chemical sciences division at Oak Ridge National Laboratory, said in a news release. “Previous models only captured one or two notes, while ours picks up the full harmony.”

According to Rice, the findings could lead to the development and application of new contrast agents for clearer MRIs in medicine and materials science. Beyond MRIs, the NMR relaxation method could also be applied to other areas like battery design and subsurface fluid flow.

“In the present paper, we developed a comprehensive theory to interpret those previous molecular dynamics simulations and experimental findings,” Dilipkumar Asthagiri, a senior computational biomedical scientist in the National Center for Computational Sciences at Oak Ridge National Laboratory, said in the release. ”The theory, however, is general and can be used to understand NMR relaxation in liquids broadly.”

The team has also made its code available as open source to encourage its adoption and further development by the broader scientific community.

“By better modeling the physics of nuclear magnetic resonance relaxation in liquids, we gain a tool that doesn’t just predict but also explains the phenomenon,” Walter Chapman, a professor of chemical and biomolecular engineering at Rice, added in the release. “That is crucial when lives and technologies depend on accurate scientific understanding.”

The study was backed by The Ken Kennedy Institute, Rice Creative Ventures Fund, Robert A. Welch Foundation and Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory.

Houston-area lab grows with focus on mobile diagnostics and predictive medicine

mobile medicine

When it comes to healthcare, access can be a matter of life and death. And for patients in skilled nursing facilities, assisted living or even their own homes, the ability to get timely diagnostic testing is not just a convenience, it’s a necessity.

That’s the problem Principle Health Systems (PHS) set out to solve.

Founded in 2016 in Clear Lake, Texas, PHS began as a conventional laboratory but quickly pivoted to mobile diagnostics, offering everything from core blood work and genetic testing to advanced imaging like ultrasounds, echocardiograms, and X-rays.

“We were approached by a group in a local skilled nursing facility to provide services, and we determined pretty quickly there was a massive need in this area,” says James Dieter, founder, chairman and CEO of PHS. “Turnaround time is imperative. These facilities have an incredibly sick population, and of course, they lack mobility to get the care that they need.”

What makes PHS unique is not only what they do, but where they do it. While they operate one of the largest labs serving skilled nursing facilities in the state, their mobile teams go wherever patients are, whether that’s a nursing home, a private residence or even a correctional facility.

Diagnostics, Dieter says, are at the heart of medical decision-making.

“Seventy to 80 percent of all medical decisions are made from diagnostic results in lab and imaging,” he says. “The diagnostic drives the doctor’s or the provider’s next move. When we recognized a massive slowdown in lab results, we had to innovate to do it faster.”

Innovation at PHS isn’t just about speed; it’s about accessibility and precision.

Chris Light, COO, explains: “For stat testing, we use bedside point-of-care instruments. Our phlebotomists take those into the facilities, test at the bedside, and get results within minutes, rather than waiting days for results to come back from a core lab.”

Scaling a mobile operation across multiple states isn’t simple, but PHS has expanded into nine states, including Texas, Oklahoma, Kansas, Missouri and Arizona. Their model relies on licensed mobile phlebotomists, X-ray technologists and sonographers, all trained to provide high-level care outside traditional hospital settings.

The financial impact for patients is significant. Instead of ambulance rides and ER visits costing thousands, PHS services often cost just a fraction, sometimes only tens or hundreds of dollars.

“Traditionally, without mobile diagnostics, the patient would be loaded into a transportation vehicle, typically an ambulance, and taken to a hospital,” Dieter says. “Our approach is a fraction of the cost but brings care directly to the patients.”

The company has also embraced predictive and personalized medicine, offering genetic tests that guide medication decisions and laboratory tests that predict cognitive decline from conditions like Alzheimer's and Parkinson’s.

“We actively look for complementary services to improve patient outcomes,” Dieter says. “Precision medicine and predictive testing have been a great value-add for our providers.”

Looking to the future, PHS sees mobile healthcare as part of a larger trend toward home-based care.

“There’s an aging population that still lives at home with caretakers,” Dieter explains. “We go into the home every day, whether it’s an apartment, a standalone home, or assisted living. The goal is to meet patients where they are and reduce the need for hospitalization.”

Light highlighted another layer of innovation: predictive guidance.

“We host a lot of data, and labs and imaging drive most treatment decisions,” Light says. “We’re exploring how to deploy diagnostics immediately based on results, eliminating hours of delay and keeping patients healthier longer.”

Ultimately, innovation at PHS isn’t just about technology; it’s about equity.

“There’s an 11-year life expectancy gap between major metro areas and rural Texas,” Dieter says. “Our innovation has been leveling the field, so everyone has access to high-quality diagnostics and care, regardless of where they live.”

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