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Superconductors are the future. We are how they get built.

Every superconducting magnet, cable, and qubit is limited by how cold it has to run. Programs pay us today, and our licenses are set up to earn a royalty on every machine built with our materials and processes.

Rows of data-center racks fed by a superconducting power line, rendered
Development contract
AI
With a major AI company
IP
20+
Patent filings, issued and pending, licensed exclusively
Capacity
4 of 7
Partner lab and pilot benches under contract, of those lined up
Theory since
2006
The Modulated Electron Lattice (MEL) framework, licensed exclusively

The engine

The platform learns from every program.

We run active learning on paid programs, so each one leaves the models sharper for the next.

Each program

  1. Predict

    GPU sweeps and generative models rank what to try.

  2. Make

    We make samples at Berkeley and with partners.

  3. Measure

    We measure them at the operating point a device needs.

  4. Learn

    Every result retrains the models.

Proprietary data

Every result is kept, hit or miss.

The next program starts from all of it.

  • Hit
  • Miss

Schematic of active learning, not a program result.

The data moat

We collect data nobody else has.

Published dataOur data
What it recordsMostly what workedWhat worked, and what did not
Where it was measuredConditions the authors choseThe operating point a device needs
What it coversThe materialThe material, what it touches, and how it was made
How it changesFixed at publicationGrows with every program

Customers own their inputs, and we agree data rights for each program. What the models learn carries into every program after.

Where it points

The four limits we are going after.

  • Temperature

    The warm-room gap

    The best durable record is still 158 kelvin short of a warm room.

  • Field

    Stronger magnets

    Compact fusion and the next generation of MRI both need them.

  • Loss

    Lower-loss power

    AI data centers and the grid need cables that waste less power.

  • Coherence

    Longer-lived qubits

    Superconducting quantum computers need better films and interfaces.

The business

How it fits together.

Built with

  • Exclusive license

    Hyunsung TNC

    MEL theory and its patents

  • Pilot manufacturing

    CAN Superconductors

  • Measurement

    Georgia Tech, UIUC, Brookhaven, WMI

SuperMatics

  • Platform
  • Lab work
  • IP

Who pays

  1. Revenue today

    Development programs

    Hardware teams Program fees

    Development contract with a major AI company

  2. Next

    Platform licenses

    R&D teams License fees

    Run by our team today, with customer access planned

  3. At scale

    Materials and process licensing

    Manufacturers Royalties

    20+ patents issued and pending

Milestones

What we have done so far.

  • Major AI company under contract
  • Five proposed materials in synthesisNone has yet been independently established as superconducting.
  • Provisionals on file
    • Wilson Sonsini
  • Accepted into BADASS Labs
    • BADASS Labs
  • Joined the Plug and Play cohort
    • Plug and Play

  • Went live with CAN Superconductors
    • CAN Superconductors
  • Independent PRL result, consistent with MELAn independent experiment, with no involvement from SuperMatics. It does not validate the entire framework.

Team

Who is building it.

  • Charlie MoonCo-founder · Chief Executive Officer
  • Davis RensFounder
  • Dr. Jaewhan KimChief Technology Officer

Where our team has worked and studied

  • Rigetti Computing
  • UC Berkeley
  • Karlsruhe Institute of Technology
  • Harvard
  • MIT
  • Illumina
  • KOPEX USA
  • Georgetown Law
  • HP
Full bios

The deck has the round, the plan, and the numbers.

Request it here, or write to us directly.