Houston startup launches innovative chat tool on its mission to democratize AI

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ThirdAI's new PocketLLM app is free to use and completely secure. Photo via Getty Images

Artificial intelligence has a big potential to disrupt the technology industry, and one Houston company that was founded by a computer science professor at Rice University, is fast on its way to help lead that future now in a convenient and affordable way.

Founded by Anshumali Shrivastava and Tharun Medini, a recent Ph.D. who graduated under Shrivastava from Rice's Department of Electrical and Computer Engineering, ThirdAI is building AI deep learning tools that aim to be sustainable and scalable to fit the changing needs of the industry. The company is on a mission to democratize AI, Shrivastava tells InnovationMap.

Shrivastava likes to use the word efficiently when describing what makes ThirdAI different, and how its programs can teach AI via multiple avenues to be what he refers to as “1,000 times more efficient.”

“The carbon footprint of these models are off the charts, and so expensive,” Shrivastava. “We believe this could be made efficient. … We use the same ideas that were developed, but we do it on a massive scale.”

ThirdAI's latest tool is a multilingual ChatGPT-like AI training tool PocketLLM app. Announced earlier this month, the tool is free. According to the company, users have access to a personalized chatbot that understands what the user is searching within documents, and can be fine-tuned to help elaborate your thoughts through a neural search.

ThirdAI's PocketLLM app is free to use. Image courtesy of ThirdAI

The app is private and secure and runs on deep-learning algorithms according to Vinod Iyengar, head of product at ThirdAI, and no one — not even ThirdAI — has access to the documents except the user.

“Tools exist to help people search text files, but that requires sharing your data with third parties,” says Iyengar in a news release. “Our solution is private and secure, powered by deep learning algorithms. And it returns results lightning fast.”

The process includes the user installing the app, uploading any text document files, and clicking "train." Minutes later, you have an AI tool that can process the information in those documents.

“The neural search encourages you to elaborate on your thoughts with details in the discover window and see the difference in results,” says Shrivastava in the release. “It can also be fine-tuned to your tastes by selecting the relevant option and hitting the update button to re-train."

In September of 2021, ThirdAI — pronounced "third eye" — raised $6 million in seed funding. The round was invested in by three California-based VCs — Neotribe Ventures and Cervin Ventures, which co-led the round with support from Firebolt Ventures. The technology ThirdAI is working with comes from 10 years of deep learning research and innovation. The company's technology has the potential to make computing 15-times faster, the company reports.

Anshumali Shrivastava is an associate professor of computer science at Rice University. Photo via rice.edu

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This Houston startup has a game-changing technology for deep learning. Photo via Getty Images

Houston artificial intelligence startup raises $6M in seed funding

money moves

A computer science professor at Rice University has raised seed funding last month in order to grow his company that's focused on democratizing artificial intelligence tools.

ThirdAI, founded by Anshumali Shrivastava in April, raised $6 million in a seed funding round from three California-based VCs — Neotribe Ventures and Cervin Ventures, which co-led the round with support from Firebolt Ventures.

Shrivastava, CEO, co-founded the company with Tharun Medini, a recent Ph.D. who graduated under Shrivastava from Rice's Department of Electrical and Computer Engineering. Medini serves as the CTO of ThirdAI — pronounced "third eye." The startup is building the next generation of scalable and sustainable AI tools and deep learning systems.

"We are democratizing artificial intelligence through software innovations," says Shrivastava in a news release from Rice. "Our innovation would not only benefit current AI training by shifting to lower-cost CPUs, but it should also allow the 'unlocking' of AI training workloads on GPUs that were not previously feasible."

The technology ThirdAI is working with comes from 10 years of deep learning research and innovation. The company's technology has the potential to make computing 15-times faster.

"ThirdAI has developed a breakthrough approach to train deep learning models with a large number of parameters that run efficiently on general purpose CPUs. This technology has the potential to result in a gigantic leap forward in the accuracy of deep learning models," per and announcement from Cervin Ventures. "Our investment in ThirdAI was a no-brainer and we are fortunate to have had the opportunity to invest."

Anshumali Shrivastava is an associate professor of computer science at Rice University. Photo via rice.edu

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Houston unicorn closes $421M to fuel first phase of flagship energy project

Heating Up

Houston geothermal unicorn Fervo Energy has closed $421 million in non-recourse debt financing for the first phase of its flagship Cape Station project in Beaver County, Utah.

Fervo believes Cape Station can meet the needs of surging power demand from data centers, domestic manufacturing and an energy market aiming to use clean and reliable power. According to the company, Cape Station will begin delivering its first power to the grid this year and is expected to reach approximately 100 megwatts of operating capacity by early 2027. Fervo added that it plans to scale to 500 megawatts.

The $421 million financing package includes a $309 million construction-to-term loan, a $61 million tax credit bridge loan, and a $51 million letter of credit facility. The facilities will fund the remaining construction costs for the first phase of Cape Station, and will also support the project’s counterparty credit support requirements.

Coordinating lead arrangers include Barclays, BBVA, HSBC, MUFG, RBC and Société Générale, with additional participation from Bank of America, J.P. Morgan and Sumitomo Mitsui Trust Bank, Limited, New York Branch.

“As demand for firm, clean, affordable power accelerates, EGS (Enhanced Geothermal Systems) is set to become a core energy asset class for infrastructure lenders,” Sean Pollock, managing director, project Finance at RBC Capital Markets, said in a news release. “Fervo is pioneering this step change with Cape Station, a vital contribution to American energy security that RBC is proud to support.”

The oversubscribed financing marks Cape Station’s shift from early-stage and bridge funding to a long-term, non-recourse capital structure, according to the news release.

“Non-recourse financing has historically been considered out of reach for first-of-a-kind projects,” David Ulrey, CFO of Fervo Energy, said in a news release. “Cape Station disrupts that narrative. With proven oil and gas technology paired with AI-enabled drilling and exploration, robust commercial offtake, operational consistency, and an unrelenting focus on health and safety, we have shown that EGS is a highly bankable asset class.”

Fervo continues to be one of the top-funded startups in the Houston area. The company has raised about $1.5 billion prior to the latest $421 million. It also closed a $462 million Series E in December.

According to Axios Pro, Fervo filed for an IPO that would value the company between $2 billion and $3 billion in January.

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This article first appeared on EnergyCapitalHTX.com.

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.”

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