Neuralix provides a unified AI platform that converts high‑volume operational data from critical infrastructure into real‑time intelligence, helping energy, manufacturing, and oil‑and‑gas organizations improve uptime, safety, and efficiency. The system applies signal processing and advanced analytics to SCADA, PLC, and plant data streams to detect anomalies, stabilize production, and reduce downtime. It is used by multiple enterprise clients and partners across these sectors.
Funding
$500K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Critical infrastructure such as energy plants, manufacturing lines, oil‑and‑gas facilities, and water systems generate massive streams of operational data that are often fragmented, noisy, and under‑utilized. Without real‑time analysis, anomalies go undetected, leading to unplanned downtime, safety incidents, and inefficiencies.
Solution
Neuralix provides a unified AI platform that ingests high‑volume SCADA, PLC, sensor, and historical data from complex industrial assets and applies signal‑processing, physics‑informed models, and advanced analytics to produce continuous, actionable intelligence. The system detects early signs of equipment degradation, pressure or flow anomalies, and other failure precursors, enabling predictive maintenance and automated production stabilization. Results are delivered through secure dashboards and APIs that integrate with existing control systems, allowing operators to make data‑driven decisions without extensive manual analysis. By embedding AI directly into plant workflows, Neuralix shifts operations from reactive troubleshooting to proactive, reliability‑focused management.
Target Audience
Primary customers are operations and reliability engineers, plant managers, and asset‑performance teams in energy generation, manufacturing, oil‑and‑gas, renewable energy, and water‑management organizations that require continuous monitoring of critical assets.
Features
- Real‑time ingestion of heterogeneous plant data sources (SCADA, PLC, IoT sensors, historical logs) with edge preprocessing
- Signal‑processing and physics‑based analytics pipelines that filter noise and extract condition‑monitoring features
- Anomaly detection models tuned for rotating machinery, compressors, turbines, pumps, pipelines, and other critical assets
- Predictive maintenance alerts with confidence scores and recommended corrective actions
- Secure, web‑based operator dashboard and REST/OPC‑UA APIs for seamless integration with existing control systems
- Explainable AI outputs that link detected anomalies to underlying sensor patterns and physical parameters
- Scalable cloud‑native architecture supporting multi‑site deployments across energy, manufacturing, oil‑and‑gas, and water management sectors