Our Mission

In production environments, customers are already getting 33 percent more compute from the same power envelope. Now they can see the carbon behind every watt.

SEATTLE, Wash. — June 16, 2026 — Neuralwatt, the software company helping the AI industry get more compute from the power it already has, today launched real-time carbon reporting across its platform, building on the energy reporting and management it has offered since day one. Every AI request now returns per-request carbon and energy data alongside every response, turning what has historically been an annual estimate into a live, actionable metric.

At the current pace of AI growth, and if built and operated with today’s practices, data centers supporting AI could emit 24 - 44 million metric tons of carbon per year by 2030, equivalent to putting millions of additional cars on the road. And while most AI platforms measure usage in tokens, the metric offers zero visibility into energy consumption, grid impact, or emissions. Unlike tools that simply report energy and carbon usage, Neuralwatt measures in order to optimize, cutting energy and now carbon at the workload level, and providing a solution for both sustainability and operational efficiencies. 

"Neuralwatt has always measured the energy behind every AI request. But energy only tells half the story," said Scott Chamberlin, co-founder and CTO of Neuralwatt. "Carbon connects that measurement to the grid, the region, and the environmental cost of every workload. That data unlocks an entirely new set of decisions for teams running inference at scale."

Why It Matters

AI's energy footprint and datacenters continue to impact surrounding communities through increased energy costs and infrastructure strain. In several U.S. states and European regions, planned data centers are expected to add gigawatts of new electricity demand over the next decade, forcing utilities to consider new generation, major transmission upgrades, and in some cases, higher rates for surrounding communities.

Simultaneously, as the Corporate Sustainability Reporting Directive takes effect in Europe and Scope 3 standards tighten worldwide, the lack of granular, verifiable emissions data is becoming a primary risk to both compliance and corporate reputation. Yet until now, teams have been left to either provide coarse annual estimates that check a compliance box but drive no improvement, or forgo visibility altogether. Neuralwatt’s live carbon data shows teams exactly where energy and money are being wasted, and where efficiencies can be gained.

How It Works

Carbon intensity varies significantly by region and time of day; the same query can carry a very different carbon cost depending on where and when it runs. For example, running the same AI workload in a region powered largely by renewables versus one that depends heavily on coal can change its carbon cost substantially, with some analyses showing up to 30 times higher emissions in coal‑dominated grids.

Neuralwatt measures the actual carbon intensity of the grid powering each request in real time, using live data from Electricity Maps, and returns per-request carbon emissions alongside every response. The integration delivers granular visibility into energy consumption and emissions so teams can evaluate model performance through the lens of regional power dynamics and real-time environmental costs.

Building for AI’s Demands

Since launch, Neuralwatt has consistently doubled its inference volume every month, evidence of strong industry demand for deeper intelligence into how AI operations impact the grid and an urgency for tools that optimize energy consumption and make it visible and actionable. As organizations look to turn this visibility into long-term efficiency, the focus is shifting from simple usage to optimized performance.

"The organizations that measure and manage their energy and carbon footprint now are not just doing the right thing," said Chad Gibson, co-founder and CEO of Neuralwatt. "They are building leaner operations that cost less to run and put less pressure on the grids and communities around them. Efficiency, sustainability, and performance are not trade-offs. They are the same problem solved well, and the companies that figure that out first are at an advantage."

Neuralwatt is already developing carbon-aware routing and flexible scheduling that will direct workloads to the cleanest available infrastructure, further ensuring AI operations land lightly on the communities that host them. Real-time carbon reporting is available now to all Neuralwatt Cloud users at no additional charge. Usage analytics including daily carbon trends, per-model breakdowns, and exportable data for compliance reporting are available in the Neuralwatt dashboard. 

About Neuralwatt

Neuralwatt is AI power optimization software that sits alongside existing infrastructure, measuring and optimizing energy at the workload level. By making every watt visible, measurable, and actionable, and now every gram of carbon, Neuralwatt helps organizations get more compute from the energy they already have while reducing costs and lowering emissions. In production environments, customers have achieved 33 percent more compute from their existing power envelopes without adding new hardware. The company is backed by Microsoft, NVIDIA, and leading venture investors. For more information, visit neuralwatt.com.

Full methodology documentation is available at: portal.neuralwatt.com/docs/energy-methodology. 

Neuralwatt and Parasail share a conviction: the next gains in AI infrastructure won't come from building more, they'll come from getting more out of what already exists.

We work at the energy layer. Our platform reads GPU telemetry in real time, measures the power behind every workload, and routes compute to the most efficient hardware available. In production, that has meant 33 percent more compute from the same power envelope, with no new hardware. Parasail works at the access layer, putting the latest-gen GPU compute in teams' hands without the long contracts and procurement delays that can bottleneck progress.

Today those approaches are coming together. Neuralwatt's energy intelligence is now running in Parasail's fleet, bringing real-time thermal awareness and smarter workload placement to their infrastructure. Their hardware runs leaner, and every customer on their platform benefits. In return, Parasail's compute helps gives our team the flexibility to keep iterating and shipping even faster, which means our users see better models and sharper efficiency gains.

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AI is changing the energy profile of data centers, but the central story does not have to be one of inevitability. Data centers accounted for about 1.5% of global electricity use in 2024, and the IEA expects demand to rise meaningfully by 2030 as AI scales. That is enough to matter for grids, communities, and operators, but it is also a scale where measurement, efficiency, and better software can make a real and meaningful difference. But exactly how big is the AI and energy challenge we’re facing, and what would it take to grow AI in a way that is measurably more efficient and responsible? We dive into some of the most pressing questions being asked about AI today.