Energy AI startup chooses Houston for first U.S. office after $20M raise

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The company is known for its Orbital AI platform, which is tailored for the energy sector. Photo via solutions.kbr.com

London-based AI firm Applied Computing has announced a $20 million Series A round and a new office in Houston.

The new Bayou City office is Applied Computing’s first in the United States and part of its North American expansion. The company is known for its Orbital AI platform, which is tailored for energy operations.

The funding round was led by Houston-based KBR Inc., with participation from San Francisco-based Databricks Ventures. KBR’s investment was first announced in March.

KBR and Applied Computing have also entered into a multi-year agreement to deliver exclusive AI products for the energy sector. KBR already has integrated Orbital into its INSITE 3.0 platform for energy projects, and is also using the product for ammonia production.

Applied Computing’s Orbital platform combines physics-grounded intelligence with models across chemical engineering, time-series forecasting and language, according to the company. The system analyzes sensor readings and can recognize a facility’s equipment constraints and operator activity. The platform can also allow technicians to run simulations of how a change to a facility could affect the rest of its operations.

According to TechCrunch, Applied Computing will use the $20 million to further explore projects and deployments with the energy sector, hire engineering and research positions, and continue to expand internationally, potentially into the Middle East.

The company is also working on deals with a major U.S. stream operator, TechCrunch reports. And Applied Computing shared on LinkedIn that it plans to announce its first partnership with a major European oil company in the coming weeks.

“Yesterday we showed Orbital live in deployments at our demo day at the Energy Institute in London,” Callum Adamson, CEO and co-founder of Applied Computing, posted on LinkedIn on July 16. “Today, we're announcing the capital to scale it globally as well as the launch of our new offices in Houston and Bangalore. In the weeks following, there will be more announcements on our progress, partnerships and deployments.”

The company opened its Bangalore offices in December.

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This article originally appeared on our sister site, InnovationMap.com.

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Scotty Nyquist discuss the growth in AI data centers and the strain on the system. Photo via HARC report

Houston energy expert asks: Who pays when AI outruns the power grid?

Guets Column

For most of the past 20 years, U.S. electricity policy relied on predictable trends in demand. Electricity use, in most regions, increased gradually, forecasts were stable, and utilities adjusted the system in small steps. Power plants, transmission lines, and substations were generally added to reflect shifts in load, rather than growth, and costs were recovered through modest adjustments to customer bills.

Growth in AI data centers has disrupted this model. A single facility can add as much electricity demand as a small town. That demand comes all at once, runs continuously, and has little tolerance for outages. If electricity service drops even briefly, computation stops, and services shut down. Ironically, data centers need reliable service, a point that their emergence is driving concern around for the rest of the grid.

What the numbers say

The International Energy Agency projects global electricity consumption from data centers to double by 2030, reaching roughly 945 TWh, nearly 3 percent of global electricity demand, with consumption growing about 15 percent per year this decade. McKinsey projects that U.S. data center demand alone could grow 20–25 percent per year, with global capacity demand more than tripling by 2030.

After years of roughly 0.5 percent annual demand growth, many forecasts now place total U.S. electricity demand growth closer to 2–3 percent per year through the mid-2030s, with much higher growth in specific regions. In Texas, some forecasters are saying electricity demand could double over the next five years, a staggering 10 percent per year growth rate. What sounds incremental on paper translates into a major challenge on the ground. Meeting this pace of growth is estimated to require $250–$300 billion per year in grid investment, about double what the system has been absorbing.

Where the system starts to strain

The strain appears first in the interconnection queue. It shows up as long waits, backlogs, and delays for connecting new loads and new generation.

Before new generators or large load customers can be connected, a study is required to assess their impact on the grid, whether it can physically handle the added load, and whether upgrades are required. With AI-driven data centers, utilities face far more connection requests than they can realistically support. In ERCOT, large-load interconnection requests exceed 200 gigawatts, most tied to data centers. That amount exceeds historical norms, and it is several times larger than what can be practically studied or built in the near term.

To be clear, public utility commissions are required to study these requests because they must manage system capabilities to ensure minimal disruption. This means engineers spend time evaluating projects that may never be built, while other more commercially viable projects may wait longer for approvals. This extends timelines and makes infrastructure planning less reliable.

Why policymakers are rethinking the rules

Utilities and their regulators must decide how much generation, transmission, and substation capacity to build years before it comes online. Those decisions are based on expected demand at the time projects are approved. When it comes to data centers, by the time infrastructure is completed, they may end up deploying newer, more efficient chips that use less power than originally assumed. This can result in grid infrastructure built for a higher load than what actually materializes, leaving excess capacity that still must be paid for through system-wide rates.

That’s the central dilemma. If utilities build too little capacity, the system operates with less reserve margin. During periods of grid stress, operators have fewer options, increasing the likelihood of curtailments or outages. However, if utilities build too much, customers may be asked to pay for infrastructure that is not fully used.

In response, policymakers are adjusting the rules. In some regions, regulators are moving toward bring-your-own-power approaches that require large data centers to supply or fund part of the capacity needed to serve them or reduce demand during system stress. At the federal level, permitting reforms tied to datacenter infrastructure increasingly treat electricity as a strategic economic input.

As Ken Medlock, senior director at the Baker Institute Center for Energy Studies (CES), explains:

“Many of the planned data centers are now also adding behind-the-meter options to their development plans because they do not anticipate being able to manage their needs solely from the grid, and they certainly cannot do so with only intermittent power sources.”

Behind-the-meter (BTM) refers to power that a consumer controls on its side of the utility meter, such as on-site gas generation or a dedicated power plant. These resources allow data centers to keep operating during grid-related service. Most facilities remain connected to the grid, but the backup BTM generation serves as insurance for operating their core business.

This shifts responsibility. Utilities traditionally manage reliability across all customers by maintaining an operating reserve margin, or spare capacity. Increasingly, large-load customers manage part of their own electricity reliability needs, which changes how infrastructure is planned and how risk is distributed.

Bottom line

AI-driven load growth is arriving faster and in more concentrated places than the power system was built to accommodate. Utilities and regulators are being forced to make decisions sooner than planned about where to build, how fast to build, and which customers get priority when capacity is limited. The effects extend beyond data centers, showing up in system costs, reliability margins, competition for grid access, and pressure on communities and industries that depend on affordable and dependable power. The issue is not whether electricity can be generated, but how the costs and risks of rapid demand growth are distributed as the system tries to keep up. How regulators balance these decisions will determine who pays as AI demand outruns the power grid.

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Scott Nyquist is a senior advisor at McKinsey & Company and vice chairman, Houston Energy Transition Initiative of the Greater Houston Partnership. The views expressed herein are Nyquist's own and not those of McKinsey & Company or of the Greater Houston Partnership. This article originally appeared on LinkedIn.

Collide has rolled out RIGGS, a large language model for energy professionals. Photo via Getty Images

Houston AI startup rolls out platform to reshape oil and gas workflows

AI for energy

Houston-based Collide is looking to solve AI issues in the energy industry from within.

Co-founded by former oil roughneck Collin McLelland, the company has developed AI software for operators and field teams, shaped by firsthand oilfield experience. Its AI-native platform “retrieves and synthesizes data from authoritative sources to deliver accurate, cited, and energy-focused insights to oil and gas professionals,” according to the company.

“Oil and gas has a graveyard full of technology that was technically impressive and operationally useless,” McLelland tells Energy Capital. “The reason is almost always the same: the people who built it didn't understand what they were actually solving for. When you're an outsider, you see workflows and try to automate them. When you're an insider, you understand why those workflows exist—the regulatory constraints, the physical realities, the liability concerns, the trust dynamics between operators and service companies.”

Collide’s large language model, known as RIGGS, performed well in recent benchmarking results when taking a standardized petroleum engineering (SPE) exam, the company reports. The exam assesses understanding from conceptual terminology to complex mathematical problem-solving.

According to Collide, RIGGS achieved a score of 67.5 percent on a 40-question subset of the SPE petroleum engineering exam, outperforming other large language models like Grok 4 (62.5 percent), Claude Sonnet 4.5 (52.5 percent) and GPT 5.1 (4 percent).

RIGGS completed the test in 15 minutes, while Grok took two hours. Collide hopes over the next few months, RIGGS will receive a score between 75 percent to 80 percent accuracy.

The software could potentially help oil and gas companies produce accurate outputs and automate trivial workflows, which can open up valuable time for engineers and teams to work on other pressing matters, according to McLelland.

“Collide exists because we sat in those seats — we were the engineers, the operators, the field guys,” he says. ”RIGGS scoring higher on the PE exam versus the frontier labs isn't a party trick. It's evidence that the model understands petroleum engineering the way a petroleum engineer does, because it was built by people who do.”

RIGGS was trained on Collide’s Spindletop hardware and is supported by a vast library of information, as well as a reasoning engine and validation layer that uses logic to solve problems.

“Longer term, we see RIGGS as the intelligence layer that sits underneath every operator's workflow — not a chatbot you open in a browser, but something embedded in the tools engineers already use,” McLelland says. “The goal is to give every engineer the knowledge and pattern recognition of a 30-year veteran, on demand."

According to McLelland, Collide is already building toward reservoir analysis and production optimization, automated regulatory compliance (Railroad Commission filings, W-10s, G-10s), workover report generation, and engineering decision support in the field for near-term use cases. In March, Collide and Texas-based oil and gas operator Winn Resources announced a collaboration to automate the time-intensive process of filing monthly W-10 and G-10 forms with the Texas Railroad Commission, completing what’s normally a multi-hour task in under 30 minutes. Collide reports that Winn’s infrastructure now automates regulatory filings and provides real-time visibility into data gaps, which has reduced processing time by over 95 percent.

“Before Collide, I'd spend hours manually keying in filings,” Buck Crum, director of operations, said in a news release. “(In March), we had 50 wells to file and I was done in 20 minutes. It does the majority of the heavy lifting while keeping me in control. That human-in-the-loop approach saves meaningful time and gives us greater confidence in our compliance and reporting.”

Collide was originally launched by Houston media organization Digital Wildcatters as “a professional network and digital community for technical discussions and knowledge sharing.” After raising $5 million in seed funding led by Houston’s Mercury Fund last year, the company said it would shift its focus to rolling out its enterprise-level, AI-enabled solution.

Hadi Ghasemi, a University of Houston professor, has uncovered a method to release heat from data centers and electronics at record performance. Photo courtesy UH.

Houston researcher develops efficient method to cool AI data centers

cool findings

A University of Houston professor has developed a new cooling method that can remove heat at least three times more effectively from AI data centers than current technologies.

Hadi Ghasemi, a distinguished professor of Mechanical & Aerospace Engineering at UH, published his findings in two articles in the International Journal of Heat and Mass Transfer. The findings solve a critical issue in the growing AI sector, according to UH.

High-powered AI data centers generate huge amounts of heat due to the GPU and operating systems they use with extreme power densities, which introduce complex thermal challenges. Traditionally, cooling methods, like microchannels, which use flow and spray cooling, have had limitations when exposed to extreme heat flux, according to UH.

Ghasemi’s research, however, found a more effective way to design thin-film evaporation structures to release heat from data centers and electronics at record performance.

Ghasem’s solution coupled topology optimization and AI modeling to determine the best shapes for thin film efficiency, ultimately landing on a branch-like structure—resembling a tree.

The model found that the “branches” needed to be about 50 percent solid and 50 percent empty space for optimum efficiency, and that they could sustain high heat fluxes with minimal thermal resistance.

“These structures could achieve high critical heat flux at much lower superheat compared to traditionally studied structures,” Ghasemi said in a news release. “The new structures can remove heat without having to get as hot as previous removal systems.

Ghasemi’s doctoral candidates, Amirmohammad Jahanbakhsh and Saber Badkoobeh Hezave, also worked on the project. The team believes their results show the impact of a physics-aware, AI design and can help ensure reliability, longevity and stability of AI data centers.

“Beyond achieving record performance, these new findings provide fundamental insight into the governing heat-transfer physics and establishes a rational pathway toward even higher thermal dissipation capacities,” Ghasemi added in the release

Merab Momen, founder of AI CTO Services. Courtesy Photo

How this Houston expert helps startups turn AI hype into real impact

now streaming

Artificial intelligence is now everywhere. It is mentioned in every startup pitch deck, and every corporate roadmap claims to use it. However, many early-stage businesses struggle with the simple question, “What does AI actually mean for my business?”

In a recent podcast episode of EnergyTech Startups, Merab Momen, founder of AI CTO Services and a long time AI practitioner, explains why most founders misunderstand AI, how startups can practically apply it and why Houston is quietly becoming a serious hub for AI-driven innovation.

Filling the AI Leadership Gap

Merab’s career has spanned decades of technology transitions. He worked on neutral networks in the 1990s, constructed computer vision systems long before they were common, and helped install AI solutions inside huge industrial companies. However, he noticed a huge problem when generative AI started to explode into the mainstream-The requirement of a real partner by the founders for AI integration but inability to rely on a full-time CTO and project-based consultants.

“I really needed something which is much more engaging where I can give that partner-level advice to the founders,” he said. By giving firms on-demand access to high-level AI knowledge and expertise, his methodology enables them to analyse tools, steer clear of cost blunders and eventually transition to a permanent technology leader when the time is right.

AI is Older than Most People Think

Despite its recent rise in popularity, AI is nothing new. AI actually began in the 1950s. Merab in his conversation explained how he worked on his first AI project back in the year 1996 that worked perfectly, but the processing power wasn’t just there to make it practical. He continued how he utilized the swarm intelligence models to optimize supply chains, now referred to as MLPOs and data engineering.

From Language Models to Physical World

Much of the public conversation about AI revolves around chatbots and text generation. But Merab sees far greater potential in AI’s interaction with the physical world, especially in industrial settings. He emphasized edge computing and vision language models (VLMs) as significant advances in manufacturing and energy. This physical shift is opening doors for new opportunities for robotics, automated inspections, and industrial safety applications. Merab added that Houston is uniquely positioned for this transition.

Why Houston has an AI Advantage

Silicon Valley may dominate the AI headlines, but Merab believes Houston’s advantage lies beneath the surface. The city doesn’t lag in AI utilization; it just operates in industries where results show differently.

Machine learning isn’t new to Houston’s core industries. Energy companies, manufacturers, logistics providers, and healthcare systems have been using advanced analytics for decades. The difference lies in them innovating in industrial sectors rather than consumer technology.

What’s Next

With the AI CTO Services growing, Merab is working with startups across industries to deploy AI in practical, business-first ways.

He is more interested in assisting founders in finding answers to critical issues than following new trends.

For Houston’s energy and climate tech community, it needs to transform AI enthusiasm into real-world impact.

Listen to the full conversation with Mehrab Momin on the Energy Tech Startups Podcast to learn more.

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Energy Tech Startups Podcast is hosted by Jason Ethier and Nada Ahmed. It delves into Houston's pivotal role in the energy transition, spotlighting entrepreneurs and industry leaders shaping a low-carbon future.

A new report shows the role Texas could play as the data-center sector enters "hyperdrive." Photo via JLL.com.

Texas could topple Virginia as biggest data-center market by 2030, JLL report says

data analysis

Everything’s bigger in Texas, they say—and that phrase now applies to the state’s growing data-center presence.

A new report from commercial real estate services provider JLL says Texas could overtake Northern Virginia as the world’s largest data-center market by 2030. Northern Virginia is a longtime holder of that title.

What’s driving Texas’ increasingly larger role in the data-center market? The key factor is artificial intelligence.

Companies like Google and Microsoft need more energy-hungry data centers to power AI innovations. In a 2023 article, Forbes explained that AI models consume a lot of energy because of the massive amount of data used to train them, as well as the complexity of those models and the rising volume of tasks assigned to AI.

“The data-center sector has officially entered hyperdrive,” Andy Cvengros, executive managing director at JLL and co-leader of its U.S. data-center business, said in the report. “Record-low vacancy sustained over two consecutive years provides compelling evidence against bubble concerns, especially when nearly all our massive construction pipeline is already pre-committed by investment-grade tenants.”

Dallas-Fort Worth has long dominated the Texas data-center market. But in recent years, West Texas has emerged as a popular territory for building data-center campuses, thanks in large part to an abundance of land and energy. Nearly two-thirds of data-center construction underway now is happening in “frontier markets” like West Texas, Ohio, Tennessee and Wisconsin, the JLL report says.

Northern Virginia, the current data-center champ in the U.S., boasted a data-center market with 6,315 megawatts of capacity at the end of 2025, the report says. That compares with 2,423 megawatts in Dallas-Fort Worth, 1,700 megawatts in the Austin-San Antonio corridor, 200 megawatts in West Texas, and 164 megawatts in Houston.

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Meet the 80+ startups pitching at Houston Energy and Climate Week

Pitch Lineup

One of the highlights from Houston Energy and Climate Week is hearing directly from the up-and-coming founders working to reshape the energy landscape.

This year, dozens of startups from Brazil to Berkeley and from right here in the Bayou City will compete for cash prizes and bragging rights while showcasing their concepts at HECW pitch events. Here's who's pitching at some of the week's signature competitions. Check back after the week wraps to see who takes home the top prizes.

Cypher Pilotathon and Startup Showcase — Sept. 15 at POST Houston

At the Cypher Pilotathon, founders will give their best 7-minute pilot pitches to industry experts and a live audience, followed by Q&A. This year's event will center around the theme, "The NEW Energy Industrial Revolution." Here's who's pitching:

Houston-based Aeromine Technologies, a distributed wind turbine company
San Francisco-based Ammobia, which develops low-carbon, energy source-agnostic ammonia
Birmingham, Alabama-based Ashipa Electric, a renewable energy semiconductor and microgrid manufacturer
Houston-based BigMachine AI, an AI engineer for industrial projects
Houston-based Corrolytics, which has developed corrosion detection technology
São Paulo, Brazil-based GLR Tech, which has developed a compact, scalable, low-cost platform for industrial emissions control
Monreal-based Green Graphite Technologies, which produces battery-grade graphite in a cost-effective and sustainable manner
Boston-based KIRA, which converts industrial wastewater into ultrapure water and solids
Edinburgh-based Mocean Energy, which works to deliver renewable ocean energy to power offshore industry
Los Angeles-based Mote, which works to convert agricultural and forestry waste into clean energy
Berkeley-based Oleo, which is developing a biomanufacturing platform to transform biomass waste into carbon-negative, cost-competitive oil feedstocks for advanced fuels
Oslo, Norway-based OTee, an automation machinery manufacturer
Houston-based Resollant, which is working to produce battery-grade graphite and ultra-low-cost hydrogen
Tulsa-based RyuGen Energy Solutions Inc., which works to turn underused commercial power into distributed AI infrastructure
Berkeley-based Sunchem, which provides precision separation of critical metals from sources including e-waste, evaporator scrap, solar panels, and mining ores and concentrates

Twenty-two other startups will participate in the startup showcase. See the full list here.

Greentown Climatetech Summit — Sept. 16 at the Continental Club

Ten Greentown startups will compete for $25,000 in prizes at Greentown Climatetech Summit's signature pitch event. Judges include Dave Dreessen, of Chevron Technology Ventures’ Future Energy Fund, and Jon Greene, of New Climate Ventures. Here's who's pitching:

Houston-based AMPeers, which manufactures high-temperature superconducting wire for high-power electrification infrastructure
Detroit-based AmHyTech, which enables ambient-condition liquid ammonia handling for fertilizer and fuel applications
Houston- and Zurich-based Biosimo, which converts biomass-based ethanol into lower-carbon acetic acid and acetyls
Houston-based Capwell Services Inc., which captures methane from low-flow oil and gas vents and returns it to market
Cleveland- and Ghana-based Cocoa Potash, which extracts potassium carbonate and fertilizer from cocoa, coconut, and palm-nut waste
Houston-based Solidec, which electrolyzes air, water, and electricity into onsite hydrogen peroxide.
Houston-based Focis AI, which converts industrial laser scans into a queryable digital twin of refineries and plants
Calgary-based Kanin Energy, which develops and finances waste heat to power projects for industrial clients
San Francisco-based FelixFusion, which models grid connection points so developers can validate interconnection in minutes
Houston-based Pike Robotics, which deploys its Wall-Eye robot to inspect hazardous tanks without taking assets offline

TEX-E Student Innovators will also pitch earlier in the day-long event, and an additional five Greentown startups will compete for $1,000 during the Lightning Pitch Competition. Find more information here.

Rice Alliance Energy Tech Venture Forum — Sept. 17 at Rice University’s Jones Graduate School of Business

Houston-based companies Aquanta Vision, Capwell Services and Deep Anchor Solutions will be joined by startups from around the world to compete to be named one of the 10 Most Promising Companies at the 23rd Energy Tech Venture Forum. Additional companies will participate in office hours.

See the full list of nearly 50 companies pitching here.

Halliburton Labs Pitch Day — Sept. 18 at the Ion

Halliburton Labs Pitch Day brings together a curated group of early‑stage energy technology investors and 16 participating companies. The event is invitation‑only. Here's who's pitching:

Australia-based Aquafortus, which has developed a non-thermal liquid to liquid desalination technology for resource recovery from wastewater brine
Calgary-based Ayrton Energy, which has developed a proprietary technology that enables hydrogen to be stored within an organic liquid, which can be handled and transported like gasoline
Illinois-based Cache Energy, which is developing electrified heat and long-term energy storage
New York-based Cella, which is working to advance subsurface mineralization of CO2
Miami-based Chemergy, which has developed a patented process to convert wet organic and plastic wastes into green hydrogen
Tennessee-based Enexor BioEnergy, which is developing on-site waste-to-bioenergy conversion systems
Reno-based Espiku, which focuses on water and minerals recovery from industrially produced water
UK-based LiNa Energy, which is developing low-cost, solid-state sodium battery technology
Michigan-based Marel Power Solutions, which is developing advanced cooling technology to redefine power-stacks
California-based Mitico, which is developing technology to collect and purify carbon dioxide at the source, post-combustion, before it enters the atmosphere
Singapore-based Nandina REM, which turns end-of-life assets into new, reliable, high-performance carbon fiber materials for the aviation, aerospace and defense industries
California-based Noon Energy, which is developing a 100-plus-hour ultra-long-duration battery storage
Silicon Valley-based Proof Energy, which is commercializing next-generation metallic solid oxide fuel cell (M-SOFC) technology.
Berkeley-based Sunchem, which provides precision separation of critical metals from sources including e-waste, evaporator scrap, solar panels, and mining ores and concentrates
Singapore-based Sungreen, an advanced materials company pioneering nanotechnology-based coatings for high-efficiency, low-cost electrodes
Minneapolis-based Syncris, which is developing next-generation modular power systems designed for the most demanding environments

Read more about Houston Energy and Climate Week and its programming in Energy Capital's event preview.

KBR's Mission Technology Solutions spinoff awarded $1.1B NOAA contract

A Big Deal

Amid a major spinoff, Houston-based KBR's Mission Technology Solutions business has been awarded a five-year contract for up to $1.1 billion from NOAA’s National Weather Service to help predict and combat extreme weather conditions.

Under the follow-on Commercial Data Program National Mesonet Program (CDP NMP) contract, KBR will provide weather and observational data from commercial stations, university and research campuses, and other non-federal providers nationwide. The information collected will assist in predicting severe temperatures and high-impact weather conditions like extreme storms.

"This award underscores KBR's proven track record of delivering vital data that strengthens national forecasting capabilities," Todd May, KBR’s senior vice president of Mission Technology Solutions, said in a news release.

According to a separate release from NOAA, the contract expands upon KBR's existing relationship with the agency. KBR will work with about 70 private industry partners on services such as data recording, collection, aggregation and processing, and will lead the CDP NMP's "network of networks."

“NOAA gathers environmental information from a wide variety of sources, and a growing list of private industry partners have joined our agency to collect this vital data,” Ken Graham, director of NOAA’s National Weather Service, said in the release. “This agreement streamlines the process that turns raw data into the gold-standard forecasts that Americans depend on.”

KBR will utilize its Speed to Mission ImpactSM technology for the project to supply data from across regions, measurement types, and system configurations. Both KBR and NOAA say the expanded data collection contract will help the agency create more accurate and timely forecasts, particularly for severe weather and extreme events, while also creating a path for new weather-observation technologies.

KBR has supported the CDP NMP for more than nine years. The program will be managed in Greenbelt, Maryland.

"We're driving expanded integration of commercial sensor and data sources into this platform and are honored to know our work helps forecasters give their communities earlier warnings and more time to prepare for dangerous weather,” May added in a release.

KBR’s Mission Technology Solutions business will be rebranded as Trinzic after its planned spin-off, the company announced last month. The spin-off is expected to close in January 2027.

Trinzic will work as an independent, publicly traded company focused on technology and engineering services for the space and national security sector. KBR will remain a separate publicly traded company that will focus on sustainable technology and services to support the energy transition.

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This article originally appeared on InnovationMap.com.

Houston researchers map data center growth, trends in new interactive platform

data center development

Have you ever wondered why data centers are located where they are?

Energy experts at Rice University’s Center for Energy Studies (CES) have developed a tool to help answer that question.

Rice researchers at the CES, part of Rice’s Baker Institute for Public Policy, have created an interactive map to track data center growth and energy infrastructure in the United States.

Kenneth B. Medlock III, Miaomiao Rimmer, Anmol Mital and Beck Edwards developed the tool, known as the U.S. Data Centers and Infrastructure map. It aims to provide a comprehensive view of the factors shaping where data centers are located, from power and water costs to infrastructure, public policy and local sentiment.

“The map lets you see why data centers are being built where they are by connecting the dots between infrastructure, power costs, water availability, public policy and public sentiment across different regions,” Medlock, senior director at CES, said in a news release. “You can zoom out and look at the whole U.S. to easily realize why data centers locations are being chosen—the price of power and water matters.”

The tool maps information on data center locations against other factors like energy, water, economics and politics. It also shows existing infrastructure in the area, including electric transmission lines, power plants, and fiber-optic networks, and provides information on water stress, electricity prices and natural gas prices.

According to Rice, the map will be updated in real time and currently includes information on existing data centers and proposed data centers.

Additionally, the map provides county-level analyses of news coverage and media to explore local attitudes towards the development of data centers in communities. Users can also explore political and demographic information.

According to the Pew Research Center, most data centers that are being built will appear in rural areas, with Virginia, Texas and Georgia leading the way in the number of planned facilities. Pew’s 2026 findings also noted that 38 percent of Americans live within 5 miles of at least one operational data center.

Meanwhile, Houston and Texas are poised for continued data center growth. Other reports predict that Houston’s data center capacity could more than double by 2028. Texas is home to an estimated 400-plus data centers, according to commercial real estate services provider CBRE.

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