Industrial copilots, predictive maintenance, Vision AI, and optimization models, built by engineers who speak your plant’s language.
Volga AI Solutions builds and deploys AI systems for plants, energy assets, and manufacturing operations: from unifying scattered operational data to shipping copilots, advisors, and optimization models that run inside the control-room workflows engineers already use.
Setpoint recommendation engines, KPI & efficiency analytics, predictive maintenance, and chemical-dosing / cooling / auxiliary-load advisors. Hybrid AI and first‑principles models, integrated directly with DCS, SCADA, and historian data.
Domain-specific copilots and RAG knowledge assistants trained on your equipment, procedures, and engineering data, for operator decision support, compliance guidance, shift handover, and onboarding.
Camera- and sensor-based inspection, safety and fatigue monitoring, and anomaly / vibration analysis for early fault identification across rotating equipment and critical assets.
A federated “single data image” across orders, inventory, process, and quality data, with expert rules and heuristics codified into the data layer as the foundation for optimization and forecasting.
Selected results from deployed work.
A global power generation and O&M operator: modular AI advisors for cooling, filter replacement, auxiliary load, chemical dosing, and setpoints, integrated with cloud and OPC environments. Reduced O&M costs and validated AI + physics-based models working together in critical systems.
A regional FMCG logistics fleet: Vision AI driver-safety stack plus a bilingual AI assistant for thousands of drivers. 70% fewer manual queries, 85% safety compliance, and up to $500K saved annually in penalties and downtime.
A $500M+ global chemical-compliance leader: AI-led modernization of SDS and labeling workflows. 90–98% automation accuracy, 99.5% ETL accuracy, and zero critical defects in live deployments.
Caster planning spans 300+ interdependent variables: chemistries, grade transitions, yield rules, energy costs, logistics. Run manually, those cycles stretch 5–7 days. Our approach: unify the data image, codify expert rules, then deploy optimization models that recommend schedules and setpoints to maximize net production.
For a U.S. restaurant-intelligence firm, three autonomous GenAI agents replaced a 200-person data-collection operation, cutting cycle time from ~1 month to ~10 minutes at ~90% lower cost. The same agentic patterns apply to document-heavy industrial workflows: permits, procedures, and compliance records.
A single high-value problem, scoped fast. First working results in weeks, proving efficiency gains and building trust before scaling.
Cross-functional pods (ML, data, process engineers, DevOps) aligned to your sprint cycles, with secure VPN, client-side Git, and full IP control.
Fully managed engineering organizations delivering 30–70% cost savings with high retention, proven with U.S. enterprise software leaders.
“The future of AI in infrastructure doesn’t start with a massive overhaul. It starts with one high-value application, deployed to solve a clear problem, prove efficiency gains, and build trust. Once impact is demonstrated, we expand, until AI becomes part of every system you run.”
The Volga philosophyAsk us for a walkthrough of our industrial AI advisors, driver-safety Vision AI, or caster optimization work: live examples, real numbers.
Talk to our team