Products

the full stack

One deterministic, auditable substrate, applied where being wrong is expensive. Every product signs what it produces.

Flagship

Probe56

AI model health platform

Full diagnostic scan across 56 functional elements and 5 dimensions. Targeted repair with zero measured collateral. Ed25519-signed certificate proving model health before and after. Air-gapped. No outbound calls. No customer data required.

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Guardian

Deterministic Safety Classifier.

Blocks prompt injections, jailbreaks, and unsafe inputs in under 5ms. Zero GPU. Standalone safety layer. Always on. Deterministic ruleset. Zero false positives.

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Gyro

Real-Time Drift Monitor.

Monitors every inference at the neuron level. Detects model drift before it reaches production. Confidence score on every answer. Calibrated per deployment. Neuron-level, not output-level.

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GI Engine

Cryptographic Auditability Substrate.

Ed25519-signed, tamper-evident record of every AI action. Live in production at app.growing-intelligence.com, and the reference implementation of Verifiable Process Infrastructure.

The VPI framework is defined formally in four axioms with three theorems establishing soundness, necessity and sufficiency. Eleven regulatory regimes — including SOX, DORA, SEC 17a-4, MiFID II, GDPR and BCBS 239 — are shown to require properties no existing tool provides. The paper was cryptographically signed by the system it describes.

Zenodo DOI 10.5281/zenodo.19921021

GI-IAC

InvoiceAtomConductor.

Decomposes and verifies invoices at atomic scale, with a conductor that monitors every component in real time: components emit signals, the conductor evaluates them against deterministic rules, signs the verdict, and stores it for public verification. A missing verdict is itself the alarm.

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Monitor

Privacy & business monitoring.

Continuous monitoring built on the same signed-entity substrate, for teams that need an auditable record of what was observed and when — not just a dashboard that claims it.

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BIO56

Research

Biological data decomposition.

Decomposes complex biological datasets into auditable signals using a deterministic 7-law classification cascade — 8 atom types × 7 laws = 56 elements. Every measurement is a mathematical formula: no AI, no trained models, no hyperparameters.

941 biological entities from 4 independent data domains — 671 cancer-gene DNA sequences (NCBI), 185 BRCA1-associated protein structures (RCSB PDB), 1,904 breast cancer patients (METABRIC cohort) and 84 live-cell DIC microscopy frames (Cell Tracking Challenge) — decomposed into 54,986,846 atoms. 19 genes were found across domains automatically, including a 3-way BRCA1 identity proof with 487 independent occurrences across DNA, protein and clinical data.

Zenodo DOI 10.5281/zenodo.21394366

ROBO56

Research

Universal robotic sensor decomposition.

Applies the same 8-atom-kind engine proven on biological data to real robotic sensor streams, across platforms that share no hardware — turning raw sensor output into signed, tamper-evident atoms.

10 sensors across 2 platforms — an autonomous vehicle (nuScenes: LiDAR, radar, camera, ego pose, calibration) and a drone (M3ED: Ouster LiDAR, dual IMU, stereo+RGB camera, event camera, SE3 pose) — decomposed into 74,373,570 atoms from 1,229 real entities. 10/10 sensors deterministic, 825/1,229 byte-exact round-trip, 2/2 tamper attempts detected with 0 false positives, and a cross-domain Identity proof verified against ground truth.

Zenodo DOI 10.5281/zenodo.21409175

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Enterprise access runs against models you already host. Tell us what you run and what it has to prove.

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