FIELD GUIDE
Pre-Winter Assessment: District Heating Network Readiness
Structured pre-winter risk assessment framework for municipal district heating networks — prioritizing sections for inspection before the heating season.
Deploy AI That
Delivers Real ROI
From predictive demand forecasting and multi-spectral vision to autonomous procurement agents — we turn proven AI research into production systems that generate measurable returns in 30–90 days.
Strategic Engineering // Florida Registry L26000104293
What We DeployProduction-Ready AI
Production-Ready AI
That Delivers ROI
Five battle-tested solutions built on our proprietary stack. Each can be piloted in 30–60 days and scaled enterprise-wide.
Not sure which solution fits your business best?
Proven in Production
Real Results. Real ROI.
28–42%
improvement in forecast accuracy
E-commerce Demand Intelligence
Demand forecasting and AI-powered decision engine for online marketplaces and e-commerce sellers.
Reduced overstock by 34% and stockouts by 41% on high-volume platforms.
Demand ForecastingMarketplaces30-day pilot
19–37%
reduction in procurement costs
Intelligent Procurement & Supply Chain
Autonomous supplier discovery, price trend prediction and seamless ERP integration for warehouses and modern supply chains.
Autonomous AgentsSupply ChainERP Integration
31–53%
reduction in unplanned downtime
Acoustic Intelligence
Early fault and leak detection using acoustic emission analysis and P-F curve modeling for critical industrial assets.
Predictive MaintenanceIndustrial IoTRisk Reduction
47–68%
fewer quality defects
Multi-Spectral Vision Intelligence
Advanced UV + IR multi-spectral inspection with real-time edge AI for quality control across manufacturing and industrial applications.
Computer VisionQuality ControlIndustrial Inspection
Proven ProcessFrom Assessment to ROI
From Assessment to ROI
in 30–90 Days
No endless consulting. No failed pilots.
We deliver production AI fast — with measurable business impact at every step.
01
Week 1
AI Readiness Assessment
Deep-dive discovery session + technical audit. You receive a personalized AI Maturity Score, prioritized use cases, and clear ROI projections.
Key Deliverables
AI Maturity Report
ROI Estimate
Recommended Pilot
02
Weeks 2–6
Pilot & Proof of Value
We deploy one high-impact solution in a controlled environment with your real data to prove measurable ROI.
Key Deliverables
Live Working Pilot
Performance Dashboard
Measured ROI
03
Weeks 7–12
Full Integration & Scaling
Seamless integration with your ERP, marketplaces, or industrial systems. Team training and production-ready pipelines.
Key Deliverables
Enterprise Deployment
Agentic Workflows
Knowledge Transfer
04
Month 4+
Continuous Optimization
Ongoing monitoring, model retraining, and expansion to new use cases. We stay with you as a long-term AI partner.
Key Deliverables
Monthly ROI Reports
AI Capabilities Roadmap
Dedicated Success Manager
Research & Insights
Whitepapers & Case Studies
CASE STUDY
False Positive in Acoustic Leak Detection of a Flooded Heating Pipeline: A Case Study in Hybrid AI Diagnostics
When ensemble AI models and a third-party correlator all flag a leak on a flooded 336 m district heating line, hybrid PNR (8.64) and phase coherence (0.4%) produce the correct no-excavation verdict.
RESEARCH PAPER
Vibroacoustic Diagnostics of Degradation and Wall Thinning in Pressurized Pipelines: From Physical Wave Propagation Models to a Hybrid DSP-Deep Learning Pipeline
Field-validated RIVIXI Diagnose module maps corrosive wall thinning (10–18.5% loss) on a ø426×7 mm district heating line — converging with UT measurements within 3.5% while ruling out active leakage.
RESEARCH PAPER
Utilizing Zero-Crossing Rate (ZCR) for Acoustic Leak Detection in Pipelines: From Empirical Models to a Physically Grounded DSP Pipeline
How Zero-Crossing Rate (ZCR) verification in RIVIXI AI v1.3 distinguishes hydrodynamic leak hiss from impulsive mechanical false alarms — reducing FPR by 13.25% on 113 field recordings.
CASE STUDY
Overcoming Data Chaos: How Machine Learning Compensates for Inaccurate Utility Records
How Decision Fusion algorithms process messy utility maintenance logs and GIS records to achieve 93.88% Recall on pre-failure zone detection.
RESEARCH PAPER
Topological AI-Analysis vs. Classical Cross-Correlation: Overcoming Legacy Defectoscope Vulnerabilities
How modern neural network algorithms eliminate the pipeline false alarm scalability barrier inherent in the direct reengineering of classical non-destructive testing.
RESEARCH PAPER
Adapting an Ultrasonic Diagnostics AI Platform to Legacy Hardware: Dynamic DSP Pipeline Reengineering
How Rivixi Lab overcame Nyquist limit collisions and legacy sensor constraints to integrate SebaKMT and Kaskad-3 detectors into the RIVIXI AI v1.3 SaaS platform.
RESEARCH PAPER
Improving Pipeline Failure Prediction via Data Sanitization, Hyperparameter Optimization, and Boosting Blending Ensembles
How a multi-model blending ensemble combined with rigorous data sanitization improved district heating and water pipeline risk prediction, achieving a ROC-AUC of 0.8879.
RESEARCH PAPER
Seeing Sound: A Computer Vision Approach to Ultrasonic Leak Detection in Industrial Pipelines
How converting ultrasonic signals into Mel-Spectrograms and applying ensemble neural networks overcame the limitations of traditional heuristics in noisy industrial environments.
RESEARCH PAPER
AI vs. Metallography: Accelerating Outage Inspection in 2.25Cr-1Mo Steel Pipelines via MBN-RVX-AI
MBN-RVX-AI replaces slow replica metallography during outages with cloud AI screening—over 92% accuracy on 2.25Cr-1Mo steel microstructural degradation.
CASE STUDY
Autonomous AI Agents in Tech Support: The ProstorHelp Architecture
How moving from scripted chatbots to autonomous ReAct agents with Advanced RAG enables zero-hallucination tech support for complex enterprise software.
RESEARCH PAPER
Application of Hybrid ML Models for Pipeline Failure Prediction
A hybrid machine learning architecture combining static pipeline characteristics with temporal accident history to forecast failures in urban heat and water supply systems.
The Minds Behind Rivixi LabBuilt by Researchers.
Built by Researchers.
Delivered by Engineers.
Our team has spent over 15 years turning cutting-edge AI research into production systems that generate real ROI.
Aleksandr Ivanaiskii
Founder, RIVIXI LLC | AI Systems Architect (Industrial AI)
PhD in Materials Science • 8 patents • 90+ publications
Bridging over 20 years of hands-on experience in materials science, industrial systems, and non-destructive testing with modern AI to build production-ready SaaS solutions for manufacturing, quality inspection, and industrial data analytics.
Connect on LinkedIn →
Sergei Shipilov
Co-Founder & AI Architecture Lead | AI Systems Architect
Senior AI Engineer · Production systems & live deployment
Senior AI Engineer and architect of production-grade AI pipelines. Sergei bridges the gap between R&D and live deployment. He specializes in building scalable, high-performance systems: multi-agent orchestration, low-latency edge inference, and hybrid LLM + Computer Vision deployments.
Expertise in real-time WebRTC pipelines and end-to-end automation for business: from demand forecasting to autonomous procurement and multispectral quality control.
Ready to work with the team that actually builds and ships production AI?