MJolnir Photonics Labs develops a holographic AI platform that runs on standard CPUs, eliminating the need for GPU farms and costly training runs. Their solution keeps data, knowledge, and decision-making under the user’s control, providing explainable answers with source receipts and scores, and operates without any model training, enabling organizations to own and audit their intelligence.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations rely on large GPU‑based foundation models that require costly, multi‑month training cycles and force them to rent intelligence from external providers. This creates strategic dependency, opacity in decision‑making, and risks to data and institutional knowledge.
Solution
Mjolnir Photonics Labs offers a holographic AI platform that runs entirely on standard CPUs, eliminating the need for GPU farms and the associated training expenses. The system uses a sparse ternary vector‑symbolic substrate called Entangled Halo to encode and retrieve knowledge deterministically, providing each answer with a verifiable source, confidence score, and correction log. By keeping data, knowledge, and decision processes under the user’s control, the platform delivers secure, explainable outputs without the traditional training barrier, enabling organizations to own and audit their intelligence.
Target Audience
Primary customers are enterprises, government agencies, and other institutions that require secure, auditable AI while retaining full ownership of their data and knowledge assets.
Features
- CPU‑only inference eliminates GPU hardware and O(n²) attention costs
- Training‑free operation leverages pre‑encoded holographic knowledge bases
- Sparse ternary vector‑symbolic representation ensures deterministic retrieval with provenance
- Every response includes a receipt showing source, confidence score, and any corrections
- Data, knowledge, and decision logic remain on‑premise or within a controlled environment
- Architecture supports air‑gapped deployment for high‑security environments