Service

Continuous Monitoring & Audit Trails

Real-time monitoring and immutable audit trails ensuring complete AI system governance, compliance tracking, and operational transparency for enterprises.

Energy & Utilities
Utility Infrastructure • Edge AI • Sovereign Intelligence

A single firmware update bricked 73,000 smart meters in Plano, Texas. The city hired 20 temp workers to read meters by hand. Cost: $765,000. 📡

73K
Smart meters knocked offline by a single firmware update in Plano deployment
Utility AMI Incident Report
$9M
Repair liability from 8% systemic meter failure rate across utility networks
AMI Financial Impact Assessment
View details

The Silent Crisis of Advanced Metering Infrastructure

A single failed firmware update knocked 73,000 smart meters offline. Memphis faces a $9M repair bill. Meters marketed with 20-year lifespans are failing system-wide across global deployments.

SMART METERS FAILING SILENTLY

Utilities invested billions in IoT metering promised to last 20 years but the software-hardware interface fails in half that time. Silent data corruption from NAND flash degradation erodes billing accuracy while 470K transmitters failed prematurely in a single metro.

SOVEREIGN GRID INTELLIGENCE
  • Predictive anomaly detection monitoring high-frequency IoT sensor data to identify failures before they occur
  • Automated firmware vulnerability scanning and functional verification using private LLMs for black-box analysis
  • Full inference stack deployed on-premise with zero data egress protecting sensitive grid architecture data
  • LoRA-based fine-tuning on proprietary utility corpus achieving 15% accuracy increase for domain-specific tasks
Predictive MaintenanceEdge AISovereign DeploymentIoT AnalyticsFirmware Security
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Automotive
Enterprise AI Security • Neuro-Symbolic Architecture

AI agreed to sell a $76,000 Tahoe for $1. No takesies backsies. 💸

$76K → $1
Tahoe sold via injection
Dec 2023
100%
Enterprise Liability for AI Misrepresentations
Moffatt v. Air Canada
View details

The Authorized Signatory Problem

Chatbots sold a $76K Tahoe for $1 and hallucinated refund policies. Enterprises face 100% liability for AI misrepresentations per Moffatt ruling.

THE PROMPT INJECTION ATTACK

Prompt injection hijacked Chevy's chatbot to agree to $1 sale. No business logic validated the offer. Enterprises are 100% liable for AI misrepresentations.

NEURO-SYMBOLIC 'SANDWICH' ARCHITECTURE
  • Neural Ear extracts intent from queries
  • Symbolic Brain validates business rules deterministically
  • Neural Voice generates responses from sanitized
  • Semantic Routing with RBAC policy validation
Neuro-Symbolic AIPrompt Injection DefenseSemantic RoutingNVIDIA NeMo GuardrailsOWASP LLM Top 10NIST AI RMF
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Housing & Real Estate
Housing & Real Estate AI Compliance

SafeRent's AI never counted housing vouchers as income. The $2.2M settlement changed tenant screening forever. 🏠

$2.28M
settlement in Louis v. SafeRent for algorithmic discrimination
Civil Rights Litigation Clearinghouse (Nov 2024)
113 pts
median credit score gap between White (725) and Black (612) consumers
DOJ Memorandum, Louis v. SafeRent
View details

The Deep AI Mandate

Automated tenant screening that relies on credit scores as 'neutral' predictors systematically excludes Black and Hispanic voucher holders, creating algorithmic redlining.

ALGORITHMIC REDLINING

SafeRent treated credit history as neutral while ignoring guaranteed voucher income. With median credit scores for Black consumers 113 points below White consumers, the algorithm hard-coded racial disparities into housing access -- rejecting tenants statistically likely to maintain rent compliance.

FAIRNESS BY ARCHITECTURE
  • Engineer three-pillar fairness through pre-processing calibration, adversarial debiasing, and outcome alignment
  • Automate Least Discriminatory Alternative searches across millions of equivalent-accuracy configurations
  • Implement continuous Disparate Impact Ratio monitoring with automated retraining triggers
  • Deploy counterfactual fairness testing proving decisions remain identical when protected attributes vary
Adversarial DebiasingCounterfactual FairnessHybrid MLOpsLDA SearchEqualized Odds
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Healthcare & Life Sciences
AI Safety, Biosecurity & Machine Unlearning

RLHF creates brittle masks that can be removed for ~$300 (Malicious Fine-Tuning). Models 'know' bioweapons but refuse to tell you. Knowledge-Gapped AI surgically excises hazardous capabilities at weight level—functionally infants in threats while experts in cures. 🧬

~26%
WMDP-Bio Score
Veriprajna Benchmarks 2024
~81%
General Science Capability
MMLU Benchmarks 2024
View details

The Immunity Architecture: Engineering Knowledge-Gapped AI for Structural Biosecurity

RLHF creates brittle masks stripped for $300. Veriprajna pioneers Knowledge-Gapped AI: machine unlearning excises bioweapon capabilities at weight level. Models are functionally infants regarding threats while experts in cures.

BIOSECURITY SINGULARITY

RLHF creates behavioral masks, not structural safety. Malicious fine-tuning strips masks for $300 in hours. Open-weight models are permanently uncontrollable. Hazardous knowledge remains dormant in weights.

KNOWLEDGE-GAPPED ARCHITECTURES
  • RMU and SAE surgically excise hazardous capabilities at weight
  • Achieves random 26% WMDP-Bio score proving knowledge erasure
  • Maintains 81% general science capability preserving therapeutic utility
  • Jailbreak success rate under 0.1% versus 15-20% RLHF models
Machine UnlearningKnowledge-Gapped AIBiosecurity FrameworkWMDP Benchmark
Read Interactive Whitepaper →Read Technical Whitepaper →
Clinical Decision Support & Health Equity AI

Black mothers die at 3.5x the rate of white mothers. The AI meant to save them is making it worse. 🩺

90%
of sepsis cases missed by Epic Sepsis Model at external validation
Michigan Medicine / JAMA
3x
higher occult hypoxemia rate in Black patients from biased oximeters
NEJM / BMJ Studies
View details

Algorithmic Equity in Clinical AI

From biased pulse oximeters to the failed Epic Sepsis Model, clinical AI inherits and amplifies systemic racial disparities, creating lethal feedback loops.

ALGORITHMIC RACISM

The Epic Sepsis Model dropped from a claimed AUC of 0.76 to 0.63 at external validation, missing 67% of cases and generating 88% false alarms. Pulse oximeters calibrated on lighter skin overestimate oxygen in Black patients, feeding fatally biased data into AI triage. California's MDC found early warning systems missed 40% of severe morbidity in Black patients.

FAIRNESS-AWARE DEEP AI
  • Integrate worst-group loss optimization minimizing risk for the most vulnerable subgroups
  • Deploy multimodal signal fusion combining oximetry with HRV and lactate beyond biased sensors
  • Implement adversarial debiasing penalizing race-correlated features while preserving pathology detection
  • Enforce local validation with Population Stability Index audits before every deployment
Fairness-Aware Loss FunctionsMultimodal Signal FusionAdversarial DebiasingEqualized OddsPopulation Stability Index
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Sports, Fitness & Wellness
Physical AI & Signal Processing

Digital health drowns in 'Vibes'—unverifiable, self-reported data. $60B corporate wellness market with fraud problem. Users strap Fitbits to ceiling fans. 📊

99%
TCN Counting Accuracy via Periodicity Engine
Veriprajna TCN implementation Whitepaper
$60B
Corporate Wellness Market with Fraud Problem
Corporate wellness fraud studies 2024
View details

The Physics of Verification: Beyond the LLM Wrapper

Digital health drowns in unverifiable self-reported data. Temporal Convolutional Networks verify human movement physics achieving 99% counting accuracy, enabling auditable Proof of Physical Work via signal processing.

VIBES VERIFICATION CRISIS

Fitness apps log video completion without verification. Campbell's Law drives fraud: users strap Fitbits to ceiling fans. Gamification without verification creates Cheater's Dividend destroying social contracts.

TEMPORAL CONVOLUTIONAL NETWORKS
  • Human motion treated as periodic signals
  • Causal dilated convolutions enable real-time verification
  • Self-Similarity Matrices detect repetition physics class-agnostically
  • Proof of Physical Work creates auditable assets
Temporal Convolutional NetworksTCNPhysical AISignal ProcessingProof of Physical WorkHuman Activity RecognitionDigital Signal ProcessingMoveNetEdge AIGDPRHIPAACausal Convolutions
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AI Governance & Regulatory Compliance
Enterprise AI & EdTech

AI tutor validated 3,750×7=21,690. Wrong answer. LLMs hallucinate arithmetic. 2+2=5 with prompting. Need System 2 brain. 🧮

99%
PAL arithmetic accuracy
PAL research Veriprajna Whitepaper
0
Hallucinated Citations in Legal Research
Veriprajna legal deployment Whitepaper
View details

The Cognitive Enterprise: From Stochastic Probability to Neuro-Symbolic Truth

LLMs hallucinate arithmetic, validating 3,750×7=21,690 as correct. Neuro-Symbolic Architecture uses Program-Aided Language Models achieving 99% accuracy via deterministic symbolic solvers.

STOCHASTIC AI LIMITS

LLMs predict token distributions, not truth. AI tutors validated 3,750×7=21,690 error, predicting tutoring dialogue instead of mathematical logic. Pattern matching fails System 2 reasoning.

NEURO-SYMBOLIC ARCHITECTURE
  • PAL writes code for deterministic execution
  • System 1 neural combines System 2 symbolic
  • Knowledge Graphs verify computational correctness deterministically
  • EdTech, legal, finance applications ensure accuracy
Neuro-Symbolic AIProgram-Aided Language ModelsPALSymPyWolfram AlphaPyReasonKnowledge GraphsLangChainLlamaIndexReAct ParadigmModel Context ProtocolMCPProperty GraphsBayesian Knowledge TracingBloom's TaxonomySymbolic ExecutionDeterministic AI
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AI Security & Resilience
Enterprise Cybersecurity & Software Resilience

A single misconfigured file crashed 8.5 million Windows systems. Cost: $10 billion. 💥

$10B
estimated global damages from the July 2024 CrowdStrike outage
arXiv / Insurance Industry Analysis
$550M
total losses for Delta Air Lines alone, triggering gross negligence litigation
Delta v. CrowdStrike (2025)
View details

The Sovereignty of Software Integrity

The CrowdStrike outage exposed how kernel-level updates deployed without formal verification can cascade into billion-dollar enterprise failures.

KERNEL-LEVEL FRAGILITY

CrowdStrike pushed a content update to 8.5 million endpoints simultaneously without staged rollout. A field count mismatch between cloud validator (21 fields) and endpoint interpreter (20) caused an out-of-bounds memory read in Ring 0, triggering unrecoverable BSODs across global infrastructure.

FORMALLY VERIFIED RESILIENCE
  • Implement AI-driven formal verification to mathematically prove correctness before kernel deployment
  • Deploy predictive telemetry with 97.5% anomaly precision to detect out-of-bounds reads in milliseconds
  • Enforce mandatory staged rollout protocols with progressive exposure and automated kill-switches
  • Architect sovereign AI infrastructure with self-healing operations and auto-rollback capabilities
Formal VerificationAI Telemetry AnalyticsKernel SecuritySelf-Healing SystemsSovereign AI
Read Interactive Whitepaper →Read Technical Whitepaper →
ML Supply Chain Security • Shadow AI • Model Governance

Researchers found 100+ malicious AI models on Hugging Face with hidden backdoors. Poisoning just 0.00016% of training data permanently compromises a 13-billion parameter model. 🧪

100+
Malicious backdoored models discovered on Hugging Face executing arbitrary code
JFrog Research, Feb 2024
83%
Of enterprises operating without any automated AI security controls in production
Kiteworks 2025
View details

The AI Supply Chain Integrity Imperative

100+ weaponized models found on Hugging Face with hidden backdoors for arbitrary code execution. 83% of organizations have zero automated AI security controls while 90% of AI usage is Shadow AI.

ML SUPPLY CHAIN WEAPONIZED

The ML supply chain is the most vulnerable enterprise infrastructure component. Pickle serialization enables arbitrary code execution on model load while 90% of enterprise AI usage occurs outside IT oversight. As few as 250 poisoned documents can permanently compromise a 13B parameter model.

SECURE ML LIFECYCLE PIPELINE
  • ML Bill of Materials capturing model provenance, dataset lineage, and training methodology via CycloneDX
  • Cryptographic model signing with HSM-backed PKI ensuring only authorized models enter production pipelines
  • Deep code analysis building software graphs mapping input flow through LLM runners to system shells
  • Confidential computing with hardware-backed TEEs protecting model weights and prompts during inference
ML-BOMCryptographic SigningTEE ComputingSupply Chain SecurityModel Scanning
Read Interactive Whitepaper →Read Technical Whitepaper →
HR & Talent Technology
Human Resources & Talent Acquisition

Amazon's AI recruited men for 3 years. Learned gender from 'Women's Chess Club.' Scrapped the system. Black Box = Bias Amplifier. ⚖️

3+ Years
Amazon AI recruiting duration
Reuters investigation findings
0.8
Impact ratio threshold
NYC Law 144
View details

The Glass Box Paradigm: Engineering Fairness, Explainability, and Precision in Enterprise Recruitment with Knowledge Graphs

Amazon's AI discriminated against women for 3+ years. Glass Box Knowledge Graphs separate demographics from decisions, ensuring compliance and eliminating bias structurally.

AMAZON BLACK BOX

AI trained on male-dominated hiring data optimized for gender bias. Black Box found proxy variables like women's clubs. Amazon scrapped after 3 years.

GLASS BOX GRAPHS
  • Knowledge Graphs use deterministic traversal algorithms
  • Demographic nodes excluded from inference graphs
  • Skill distance measured using graph embeddings
  • Regulatory compliance with audit trail transparency
Knowledge GraphsExplainable AINeo4jGraph EmbeddingsNode2VecGraphSAGESemantic MatchingCosine SimilarityBias MitigationNYC Local Law 144EU AI ActGDPR ComplianceDeterministic ReasoningSubgraph Filtering
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Industrial Manufacturing
Circular Economy, Waste Management & Deep Tech Recycling

Millions of tons of black plastics are ejected from recycling—not because they lack value, but because NIR sensors literally cannot see them. Veriprajna's MWIR solution shifts from pixels to chemistry.

9%
Global Plastic Recycling
Industry Report 2024
90%
Black Plastic Recovery
View details

Seeing the Invisible: The Physics, Economics, and Intelligence of Black Plastic Recovery

NIR sensors cannot detect black plastics—carbon black absorbs radiation before polymer interaction. Veriprajna shifts to MWIR (2.7-5.3 µm) with cryogenic Specim FX50 sensor and 1D-CNN spectral processing, achieving 90%+ recovery rate with under 5ms latency.

NIR BLINDNESS

Carbon black absorbs NIR radiation creating zero return signal—flatline interpreted as empty belt. No spectral curve to analyze, only noise. AI wrappers cannot recover information lost at sensor layer.

MWIR CHEMICAL VISION
  • Shifts from NIR to MWIR (2.7-5.3µm) capturing polymer fundamental vibrations
  • Specim FX50 cryogenic sensor delivers 154 spectral bands at 380fps
  • 1D-CNN processes spectral signatures as signal not image achieving 90%+ recovery
  • Edge inference achieves under 5ms latency with TensorRT optimization on Jetson
MWIR Hyperspectral1D-CNN ProcessingCircular EconomySpecim FX50PLC IntegrationReal-Time InferenceGreen TechSustainable Recycling
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Material Recovery, Recycling Automation & FPGA Edge Computing

At 3-6 m/s belt speeds, 500ms cloud latency creates a 1.5-3.0m blind displacement. Veriprajna's FPGA edge AI achieves <2ms deterministic latency for 300% throughput gains.

<2ms
FPGA Edge Latency
Veriprajna Systems 2024
300%
Throughput Increase
View details

The Millisecond Imperative: Why Cloud-Based AI Fails at High-Speed Material Recovery

500ms cloud latency creates 3m blind displacement at 6m/s belt speed. Veriprajna's FPGA dataflow architecture achieves under 2ms deterministic latency with INT8/INT4 quantization, enabling 300% throughput gains and sub-millimeter ejection precision with zero jitter.

CLOUD LATENCY CRISIS

500ms cloud latency creates 3m blind displacement at 6m/s belt speed. Object moves beyond detection zone before inference completes. Non-deterministic jitter prevents synchronization. Compensation requires extended conveyors increasing CapEx and footprint.

FPGA DATAFLOW ARCHITECTURE
  • Spatial logic maps algorithm onto silicon eliminating Von Neumann bottleneck
  • INT8/INT4 quantization achieves 4-8x memory reduction with 99%+ accuracy retention
  • Zero-OS bare metal isolates critical inference from Linux scheduler jitter
  • Hardware-software co-design delivers under 2ms deterministic latency enabling sub-millimeter precision
FPGA Edge AIDataflow ComputingINT8 QuantizationZero-OS ArchitectureLatency BlindnessPneumatic SortingConveyor Belt AutomationReal-Time ControlJitter EliminationDeterministic InferenceDSP SlicesMAC OperationsTensorRTDeep Tech
Read Interactive Whitepaper →Read Technical Whitepaper →
Financial Services
Enterprise Finance & Tax Compliance

ChatGPT failed 100% of tax compliance tests. The IRS doesn't accept 'probably.' 🧮

100%
LLMs failed tax tests
Veriprajna Audit 2025
90%
Financial blogs spread misinformation
Typical Rate
View details

The Stochastic Parrot vs. The Statutory Code

Major LLMs hallucinate tax advice, citing non-existent statutes. AI trained on misinformation, not IRC code creates compliance risk.

THE CONSENSUS ERROR

LLMs train on popular misinformation, not statutory truth. Every major model failed OBBBA tests, hallucinating tax deductions and creating enterprise audit liability.

NEURO-SYMBOLIC TAX ENGINE
  • Encode IRC rules in legal DSLs
  • Knowledge Graphs map statutory relationships explicitly
  • LLM queries symbolic logic for answers
  • Full audit trail with IRS-ready documentation
Neuro-Symbolic AIKnowledge GraphsCatala DSL
Read Interactive Whitepaper →Read Technical Whitepaper →

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Veriprajna Deep Tech Consultancy specializes in building safety-critical AI systems for healthcare, finance, and regulatory domains. Our architectures are validated against established protocols with comprehensive compliance documentation.