SEALSQ, WISeQey & Eco Wave Power Demo Trusted Energy Transactions

Eco Wave Power’s wave-energy installation in Jaffa Port, Israel, recently served as the testing ground for a collaboration focused on secure energy transactions. SEALSQ Corp, WISeQey Corp, and SEALCOIN AG have signed a three-year Memorandum of Understanding with Eco Wave Power U.S. Inc to connect renewable energy production with authenticated digital representations and automated transactions. “This collaboration creates an opportunity to extend the WISeQey ecosystem into renewable energy,” says Carlos Moreira, Founder and CEO of SEALSQ.

WISeQey, SEALSQ, and SEALCOIN Demonstrate Trusted Energy Data with Eco Wave Power

This achievement moves beyond simple data transmission, establishing a foundation for machines to autonomously engage in economic actions based on real-world physical events. The collaborative effort uses SEALSQ’s secure semiconductors along with WISeQey’s expertise in digital identity and Public Key Infrastructure (PKI), and SEALCOIN’s machine communication infrastructure, to create an integrated platform. This architecture connects physical infrastructure, in this case, wave energy, to authenticated digital information and auditable transactions, a system designed to address the growing need for trust in renewable energy sourcing.

The companies also plan to integrate SEALSQ’s QS7001 post-quantum secure element and quantum-resistant cryptographic technologies, anticipating future security requirements for critical infrastructure. The demonstration’s implications extend beyond simply verifying energy production; it addresses a key challenge in connecting renewable energy sources to demanding consumers like AI data centers. As electricity demand from AI infrastructure increases, trusted digital systems are essential for enabling qualified buyers to access authenticated production information and automate transactions under pre-agreed commercial terms.

Eco Wave Power has already begun discussions with data center developers and infrastructure partners to explore potential future electricity supply opportunities, with its AI and data center arm, a member of the NVIDIA Inception program, leading the charge, SEALSQ says. “Building the energy infrastructure for AI requires both new sources of electricity and trusted systems capable of connecting those sources with customers,” said Inna Braverman, Founder and CEO of Eco Wave Power.

“Our ambition is to bring wave energy into that ecosystem. Together with SEALCOIN, SEALSQ and WISeQey, we have demonstrated how physical wave-energy production can become trusted digital information and initiate a secure, auditable transaction. We believe this creates an important foundation for a future in which wave-energy producers can securely connect with AI data centers and other energy buyers, transact under agreed commercial terms and ultimately participate directly in the digital energy economy.” WISeQey and SEALSQ, both listed on Nasdaq and the SIX Swiss Exchange, see this collaboration as a natural extension of their existing expertise.

The system’s functionality goes beyond simply exchanging information. Jonathan Llamas, Chief Product & Strategy Officer of SEALCOIN, clarified this point, stating, “Until now, machines have primarily been designed to exchange information. The collaboration will be presented at Quantum Days 2026, with a live demonstration scheduled for November 19 in Cannes, France.

This collaboration creates an opportunity to extend the WISeQey ecosystem into renewable energy, a market where secure connectivity and trusted transactions can support new digital services.

Carlos Moreira, Founder and CEO of SEALSQ
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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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