THERMOThermodynamic Software for Post-Quantum, Planet-Scale Agentic AI.
Today’s Agentic AI relies on deterministic digital hardware forcing probabilistic math through brute-force matrix multiplication. The result is an unsustainable energy crisis and a compute-cost barrier that locks billions of global consumers out of personal AI. We think this is wrong today and will be worse tomorrow if not remedied.
We are building the foundational software layer for Thermodynamic Computing—harnessing natural physical stochasticity and energy-minimization principles to run autonomous AI agents at a fraction of the energy and financial cost.
Computing with Physics,
Not Against It.
Bridging classical silicon today with thermodynamic co-processors and post-quantum security.
Face & Voice Biometrics · Personal AI Agents
ML-KEM (FIPS 203) & ML-DSA (FIPS 204)
Langevin Dynamics & Energy-Based Stochastic Sampling
Proposed architecture. Mobile thermal envelope and sub-2ms verification are supplied design targets, not independently verified measurements.
Our software runs today by mapping Langevin dynamics and thermodynamic sampling algorithms onto existing classical hardware (GPUs/NPUs), while remaining hardware-agnostic and natively ready for dedicated thermodynamic co-processors as they scale.
By aligning algorithmic probability with physical thermodynamics, we reduce compute overhead by orders of magnitude—democratizing personal AI for the global consumer market.
Autonomous agents require autonomous security. Our stack integrates Post-Quantum Cryptography (lattice-based hard math) directly into the agentic transaction layer, ensuring security against both classical and future quantum adversaries.
To validate our thermodynamic runtime in high-stakes environments, our flagship deployment is a Consumer B2B2C Face & Voice Biometric Payment Ledger:
Thermodynamic inference processes, multi-modal voice and facial vectors locally with near-zero battery and compute drain.
Every biometric authorization is wrapped in post-quantum cryptographic proofs, securing global consumer micro-transactions against future quantum decryption.
Our MVP operates on a hybrid compute model. Today, our software runtime executes physics-inspired stochastic algorithms and energy-based models on standard classical processors—dramatically reducing the matrix-multiplication overhead required for agentic probabilistic reasoning. As specialized thermodynamic and analog co-processors enter the market, our abstraction layer allows applications to offload sampling workloads natively without rewriting code.
As AI agents gain autonomy to execute financial transactions on behalf of consumers, two bottlenecks emerge: the energy cost of continuous verification and the vulnerability of legacy encryption (RSA/ECC) to quantum attacks. By pairing low-energy biometric inference with NIST-standard lattice-based cryptography at the ledger layer, we secure autonomous micro-transactions against both current fraud and future quantum decryption.
Current agentic AI relies on massive, centralised GPU clusters, creating a high per-token cost that excludes billions of users globally. By shifting inference toward energy-minimising sampling algorithms that run efficiently at the edge, we drastically reduce cloud compute dependency—making personal AI agents economically viable for everyday consumer devices worldwide.
My path to Thermodynamic Computing began around age ten, sitting downstairs pretending to read my father Matthew Yeboah Mensah’s physics books while he studied upstairs—captivated by the subjects he loved and the warmth with which he spoke of his teachers, Professor David Bohm and Professor Hiley. Decades later, building a free-to-consumer Agentic AI payments app forced me to confront how energy-intensive and costly AI can be at scale. Today, I am dedicated to building Thermodynamic Computer Software and collaborating with brilliant minds in physics—both to power our own platform and to provide the infrastructure that makes everyday, free-to-consumer Agentic AI economically viable for other businesses.
David Nana Kumi Mensah
We are actively seeking collaborators in non-equilibrium thermodynamics, stochastic differential equations, and lattice cryptography to co-publish and benchmark our open runtime primitives.
We are unlocking the next S-curve of compute efficiency while capturing the high-margin B2B2C fintech Payments and Trust market.
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