AI can recommend. VerifyAI helps you decide what to trust.
From AI-generated conclusions to evidence-backed, accountable decisions. Independent physical verification, causal explainability, and certified human-in-the-loop governance for high-consequence operations.
Why We Built VerifyAI as an Independent Layer
Understanding the fundamental distinction between standard anomaly monitoring and evidence-backed independent verification.
What does VerifyAI do?
VerifyAI acts as an autonomous, independent verification and governance layer operating alongside AI systems and Digital Twins, vetting automated recommendations against physical laws and multi-sensor evidence before action is taken.
Why does independent verification matter?
In high-consequence industrial facilities, a single false alarm can trigger $200k+ in unneeded outage penalties, while an undetected fault leads to catastrophic failure. An AI model cannot independently audit its own conclusions.
How is evidence collected and corroborated?
VerifyAI synchronizes raw telemetry across orthogonal domains: electrical load, thermodynamic gradients, hydraulic differential pressure, acoustic sound pressure, and chemical chromatography with microsecond timestamping.
How are conclusions checked?
Hypotheses are evaluated against first-principles physics equations (e.g., IEC thermal models), 2-out-of-3 voting logic, and counterfactual causal attribution to eliminate competing hypotheses and isolate sensor artifacts.
How is uncertainty communicated?
We reject opaque single-number probabilities. VerifyAI computes an explicit Evidence Convergence Index detailing physics residuals, cross-sensor agreement, and applying strict penalties for telemetry dropouts, locking out automated actions when uncertainty is high.
How is human authority preserved?
AI recommends, but never overrides human authority on critical assets. Consequential actions require explicit, authenticated operator sign-off supported by complete, reviewable evidence packs, preserving full human governance.
Why is auditability foundational?
Every observation, model lineage, physics trace, and human authorization is sealed into an immutable SHA-256 evidence manifest, providing tamper-resistant proof for regulatory bodies, insurers, and safety boards.
Live Evaluation: Real Thermal Anomaly vs Sensor False Alarm
Experience how VerifyAI evaluates a high-consequence operational decision on a substation step-up transformer. Select scenarios, inspect 3D sensors, and contrast traditional AI tripping with independent multi-modal verification.
Emergency Trip CB-110 immediately. Shed 100% plant generation.
Verified Physical Anomaly: Thermal dissipation degradation caused by Pump 2 contactor stall, not catastrophic dielectric breakdown.
Derate transformer load to 65% (26 MVA) + force auxiliary fan bank 3 & 4. Avoids trip, maintains 26 MW generation, keeps hotspot ≤ 98°C.
How VerifyAI Converts AI Suggestions into Audited Decisions
Every AI hypothesis is subjected to independent physical checks, cross-modal telemetry corroboration, and transparent uncertainty bounding before human sign-off.
Winding temperature surge observed at 118.4°C while carrying 34.8 MVA (87% rated capacity).
Telemetry ingest triggers high-priority ingestion event. The raw signal is ingested from the substation SCADA RTU with millisecond time-stamping (IEEE 1588 PTP).
Pt100 RTD reports 118.4°C (Trip threshold 120.0°C).
118.4°C34.8 MVA / 0.92 power factor with 8.2% THD current.
34.8 MVASubstation weather station reports 36.5°C ambient air.
36.5°CWhere VerifyAI Operates in the Industrial Stack
An independent verification and governance layer operating between AI predictive models and human operational authority.
VerifyAI Independent Verification Layer
VerifyAI operates as an autonomous, independent auditor alongside AI systems, cross-validating hypotheses against physical laws, sensor health, and policy.
- Thermodynamic lumped-capacitance and hydraulic differential verification
- 2-out-of-3 cross-sensor corroboration with sensor drift discrimination
- Transparent Evidence Convergence Index calculation with gap penalties
Engineering Status & Transparent Operational Limitations
Adhering to rigorous engineering honesty: we document what is actively running, what is simulated, and the explicit physical limits of each capability.
| Domain | Capability | Engineering Status | Verified Evidence | Operational Limitations |
|---|---|---|---|---|
| Evidence Ingestion | Multi-Modal Telemetry Synchronization | ● Implemented | Synchronizes thermal, electrical, hydraulic, and chemical telemetry with millisecond precision. | Requires time-synchronized edge gateways (IEEE 1588 PTP or NTP Stratum 1). |
| Physics Modeling | Thermodynamic Residual Cross-Validation | ◈ Prototype | Solves IEC 60076-7 thermal differential equations to verify hot-spot against cooling power. | Assumes homogeneous oil circulation; CFD mesh modeling not computed in real time. |
| Sensor Assurance | Sensor Drift Discrimination & Isolation | ● Implemented | Differentiates physical thermal lag from sudden stepped resistance jumps (galvanic fault). | Requires minimum 2 independent sensor channels measuring adjacent thermal zones. |
| Uncertainty Math | Evidence Convergence Index Calculation | ● Implemented | Synthesizes physics agreement, cross-sensor agreement, and baseline consistency with data-gap penalties. | Weights are calibrated per asset class; extreme weather conditions require adaptive tuning. |
| Spatial Digital Twin | 3D Power Transformer Explainer Twin | ● Implemented | Interactive WebGL 3D model with real-time sensor inspection, fan animations, and thermal shaders. | Client-side WebGL rendering; low-end mobile devices use fallback simplified geometry. |
| Human Governance | Human Authorization Gate & Override Console | ● Implemented | Blocks automated actuation for high-impact actions; requires authenticated human sign-off. | Relies on operator presence during emergency dispatch intervals. |
| Cryptographic Audit | Immutable SHA-256 Evidence Manifest | ● Implemented | Hashes raw telemetry vectors, model version hashes, verification outputs, and operator identity. | Guarantees record integrity and non-repudiation; does not guarantee factual infallibility. |
| Synthetic Testbed | Synthetic High-Frequency Fault Generators | ▲ Simulated | Simulates contactor lockup, DGA RS-485 bus dropout, and wind gust acoustic noise. | Generators operate in test simulation sandbox; not connected to live physical grid breakers. |
| Enterprise Connectors | OSIsoft PI & AspenTech IP.21 Native Connectors | ○ Planned | Direct historian adapters for high-throughput operational archive synchronization. | Currently integrated via REST/OPC UA gateways; native AF SDK driver on Q3 roadmap. |
| Cryptographic Security | Hardware Security Module (HSM) PKCS#11 Signing | ○ Planned | Hardware-rooted private key signing for regulatory compliance and non-repudiation. | Currently uses software-based SHA-256 digest; HSM appliance integration in validation. |
VerifyAI Across Nexus Industrial Digital Twins
The independent verification engine validates operational conclusions across all Nexus digital twin demonstrations.
Energy Intelligence & Substation Grid
VERIFYAI RESOLUTION:Corroborates EIS internal resistance with thermal coolant flow throttling.
Hyperscale Data Center Infrastructure
VERIFYAI RESOLUTION:Verifies Kelvin four-wire sensor calibration before approving string bypass.
Heavy Manufacturing & Precision CNC
VERIFYAI RESOLUTION:Separates tool chatter resonances from inner-race spalling defect.
Pharmaceutical Cold Chain Storage
VERIFYAI RESOLUTION:Attributes excursion to door seal micro-leakage rather than compressor failure.
Maritime & Port Environmental Monitoring
VERIFYAI RESOLUTION:Eliminates engine injector fault by correlating ocean current vector data.
Fusion Tokamak Magnet Systems
VERIFYAI RESOLUTION:Discriminates cryogenic helium bubble noise from superconductor quench.
Ready to bring independent verification to your operational AI?
Connect with Nexus principal engineers to evaluate how VerifyAI integrates with your telemetry historians, predictive models, and human operational protocols.