Ennes Labs develops privacy-first applications, quantum random number generation hardware, and convergent AI/quantum systems — grounded in the Polygonal Sequence of Common Ratios (PSCR), a proprietary mathematical framework that gives rise to native polybit computation.
Ennes Labs is a research-driven development studio focused on building products and systems at the intersection of geometric mathematics, quantum information, and practical privacy engineering.
Our work is anchored by PSCR — a proprietary mathematical framework first discovered in 2002 — which provides a deterministic convergence structure used across all of our products: from the cryptographic layer inside our messaging application, to the geometric features in our trading engine, to the scoring logic in our FPGA-based quantum hardware.
We build things that work. Our QRNG hardware is operational and producing true quantum randomness continuously. Our encrypted messaging application is approaching public launch. Our quantum operator algebra has been validated on real quantum processors. Our PSCR-Q language model, trained on consumer hardware, is outperforming standard scaling-law predictions by approximately two times across three training phases.
PSCR is a proprietary mathematical framework that assigns every polygon a deterministic convergent ratio. This structure produces a complete computational paradigm, a closed quantum operator algebra, and practical applications spanning cryptography, hardware acceleration, and geometric AI.
The Polybit — the fundamental unit of PSCR computation — carries intrinsic geometric properties enabling native parallel evaluation across multiple computational engines. Implemented on FPGA hardware with exact integer arithmetic at full precision.
A closed algebra of thirteen geometric operators, each encoding a distinct physical process. Validated on IBM Quantum hardware, with additional operators planned for next-generation quantum processor validation.
Dual-channel convergence fields driven by quantum-random photon events. Positive and shadow coupling channels work together to steer probabilistic decision-making in real time with adaptive quantum/classical scheduling.
PSCR-derived keystream generation deployed in production as an independent cryptographic layer. Complements established symmetric ciphers with geometric defense-in-depth without replacing proven standards.
Android applications and software systems built around user privacy and ownership. No tracking. No advertising. No data harvesting. Yours to keep, with lifetime updates included.
Android app that extracts clean, readable text from any web page, PDF, document, or pasted source. Strips ads, cookie banners, navigation, and trackers. Coming soon to Google Play.
Universal extraction. Any URL, PDF, DOCX, HTML, plain text, JSON, CSV, RTF, Markdown — clean readable text in seconds.
Zero data collection. No analytics, no advertising, no telemetry. Everything stays on your device. The app has no Ennes Labs servers to phone home to.
Owned for life. One-time purchase, no subscription, no DRM phone-home. Every future update included free, for as long as the application is maintained.
Seven-stage pipeline. JSON-LD detection, scored content blocks, link-density penalization, full entity decoding — extraction tuned for high recall on real-world pages.
Post-quantum encrypted messaging for Android. Hybrid post-quantum key exchange, authenticated symmetric encryption, and PSCR geometric pre-whitening — three independent cryptographic layers. No phone number, email, or real name required.
Autonomous stock trading for Android. Multi-factor signal generation with adaptive policy learning, per-symbol calibration, and PDT-aware position management. PSCR geometric computation integrated into the decision pipeline.
Real-time probabilistic decision system driven by quantum-random photon events. All thirteen PSCR operators mapped across dual convergence channels with adaptive scheduling.
Offline survival game for Android. You're a single-celled amoeba navigating ten escalating biomes — toilet bowl to backyard pond. Eat, strike, encyst, dodge. Hand-tuned bosses each stage. Persistent growth across the campaign. No ads, no tracking. Survive. Grow. Clean up the gunk.
Every Ennes Labs product — software, hardware, or research tool — is built on five non-negotiable commitments to the people who use it. These aren't marketing language. They're how we build, every time.
Read the full Ennes Labs Privacy Policy for the detailed promises behind each commitment.
Physical QRNG hardware producing true quantum randomness from single-photon timing events, feeding convergence systems and cryptographic key generation.
Laser through crystalline diffuser to avalanche photodiode. Quantum-indeterminate photon arrival times provide the entropy source.
Picosecond-resolution time-to-digital conversion captures each photon event as a high-precision timing measurement.
FPGA fabric owns measurement, PSCR convergence computation, and output — all scoring at exact integer precision.
Quantum-seeded data streams to application systems in real time over high-speed serial and network links.
PSCR-Q replaces conventional subword tokenization and flat output projection with a geometry-native architecture derived from PSCR. Tokens map to precise rational coordinates on a mathematical number line rather than arbitrary indices. Trained on consumer mining-class GPUs, the model is consistently outperforming standard Chinchilla scaling-law predictions by approximately two times.
A vocabulary of 578,371,096 tokens, each at a unique coordinate on the PSCR number line. Structural relationships between tokens are encoded in their mathematical addresses — relationships conventional architectures must otherwise learn through trillions of training tokens.
The output projection factorizes from 592 GB (physically impossible) to 217 MB — a 2,800× compression. Not an approximation: a lossless mathematical decomposition of the vocabulary into integer-neighborhood and within-gap-position predictions.
A continuous self-correction engine inspired by biological DNA repair. Fisher-weighted proofreading detects parameter drift across ten knowledge domains and applies targeted interpolation. Four-track storage topology supports branch evolution with antiPSCR rollback for rejected experiments.
All training performed on six NVIDIA P104-100 mining-class GPUs (8 GB each) over a Windows DDP cluster. Comparisons are against Chinchilla scaling-law predictions (Hoffmann et al., 2022) for matched parameter and token budgets.
Status: Manuscript prepared. Phase 3 supervised fine-tuning complete on two model generations. Codosome continuous self-correction validated in Gen 2 Phase 3.5. Gen 3 base training in progress at 422M parameters with continued geometric extensions and significantly stabilized gradient norms. Architecture details and code under preparation for release.
PSCR's quantum operator algebra was implemented in Qiskit and executed on IBM Quantum's Heron r2 superconducting processors. An ablation study across polygon geometries measured Hellinger fidelity at each entanglement stage, surfacing geometry-dependent performance and anomalous fidelity at high circuit depths. Methodology and complete results are documented in the research manuscript.
Building at the intersection of geometric mathematics, quantum hardware, and practical software — where each discipline strengthens the others.
Post-quantum encrypted applications that protect user data by default. No tracking, no advertising, no data harvesting. Cryptographic layers built on both established standards and proprietary PSCR-derived primitives.
Bridging quantum random number generation, photonic hardware, and polybit computation into systems that leverage true quantum randomness for classical decision-making and AI-guided optimization.
Advancing PSCR as a computational paradigm — from FPGA-native polybit processors to quantum operator validation to language model architecture — applying it to real products that demonstrate the framework's practical utility.
For inquiries about our products, research collaborations, or partnership opportunities.
Or email directly: info@enneslabs.com