: Our Foundation Principle
Specializing in non-autoregressive edge AI, zero-multiplication subtractive neural meshes, real-time LLM telemetry control planes, and enterprise glass-box security gateways.
A radical departure from autoregressive token generation. Replaces matrix multiplications with power-of-two (PO2) bitshifts and geometric subtractive manifolds.
All arithmetic executed via bitshifts and subtraction ($x \gg k$). Operates deterministically on bare-metal ARM/x86/RISC-V with zero GPU requirements.
Achieves 238,000 queries per second per CPU core. Closed-domain inference runs 10,000x faster than traditional transformer decoders.
Compact .otmb binary domain meshes (Python, Cardiology, Indian Classical Music) compile directly into L1/L2 CPU cache.
Full observability stack for large language models and edge agents. Provides zero-token overhead telemetry, WebGPU local acceleration, and deep perceptual diagnostics.
Stream runtime KV-cache health and layer activations without consuming LLM context window tokens.
Client-side shaders execute token verification and attention heatmaps directly inside Chrome/Edge.
Inspect offline local LLM sessions with cryptographically sealed audit trails.
Real-time 3D spatial projection of multi-head self-attention token affinity weights.
For individual AI engineers & researchers
Air-gapped clusters & private cloud
Sandwiching uninterpretable black-box models between deterministic mathematical sentinels, equipped with an Internal Safe Passage Corridor for authenticated creative traffic.
Neutralizes prompt injections, jailbreaks, and adversarial vectors before model execution.
Runs high-dimensional synthesis. Safe passage tokens allow creative bypass without false alarms.
Verifies factual outputs against discrete ALU arithmetic and Causal Lineage DAGs before user delivery.
Author: Chandramouli β’ DOI: 10.5281/zenodo.22800741 β’ License: CC-BY-4.0 (Open Access)
View Permanent DOI Record on Zenodo β
Evaluated on official Meta FLORES-200 splits using sacrebleu chrF++: