Rayven
✓ Verified ProfileOperational software for an AI-powered world.
Operational software for an AI-powered world.
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Rayven supports business intelligence for industrial and asset-intensive operations by unifying operational data from IT, OT, IoT, files, and legacy systems into a single environment. This enables real-time operational reporting, KPIs, and insights that reflect what is actually happening on sites and across assets, rather than relying on delayed, manually prepared reports or disconnected BI dashboards.
Rayven enables operational data analysis by bringing fragmented industrial data into one place and making it usable in real time. Teams can analyse performance, bottlenecks, downtime, and trends directly within operational systems, without manual data preparation, exports, or separate analytics tools. Analysis is embedded into day-to-day operations, not isolated in back-office reporting environments.
Rayven delivers workflow management designed for industrial environments. It replaces spreadsheet-driven, email-based, and manual handoffs with automated operational workflows that integrate directly with existing systems, assets, and field teams. These workflows are built around real operational processes, supporting consistency, traceability, and coordination across sites, shifts, and teams without forcing process redesign.
Rayven supports mobile operational applications by delivering made-to-fit solutions for field and site teams. These applications are designed around real operational workflows, devices, and environments - anything -, integrating live data from existing systems. Customers receive fully delivered mobile solutions without needing internal mobile development teams or relying on generic app-building platforms.
Rayven provides asset tracking capabilities by unifying data from enterprise systems, sensors, and field inputs - anything - into a single operational view. Teams gain real-time visibility into asset location, status, condition, and usage across sites. This supports better coordination, maintenance planning, and operational decision-making without replacing existing asset or maintenance systems.
Rayven enables operational data visualisation by presenting real-time views of assets, processes, and workflows built directly on unified industrial data. Visualisations are embedded within operational systems and applications, ensuring teams see current, actionable information that supports decisions and action, rather than static charts created from delayed or manually consolidated data.
Rayven applies artificial intelligence in practical operational contexts. By unifying industrial data first, Rayven enables AI-driven capabilities such as anomaly detection, prediction, optimisation, and automated decision support. These capabilities are embedded directly into operational systems and workflows, focusing on improving day-to-day performance rather than abstract experimentation or standalone AI tooling.
Rayven handles data extraction across complex industrial environments, pulling information from IT systems, OT platforms, IoT devices, files, and legacy tools - anything. Extracted data is normalised and made available in real time for operational use, automation, and applications, eliminating manual exports, fragile scripts, and point-to-point data extraction approaches. Discover more at rayven.io
Rayven provides ETL capabilities designed for operational use. It continuously ingests, transforms, and unifies industrial data from multiple sources, supporting real-time visibility and automation rather than batch-only reporting. ETL is embedded as part of a broader operational system, removing the need for separate data engineering pipelines or standalone ETL tooling.
Rayven functions as integration software for industrial operations by connecting ERP, SCADA, WMS, BMS, IoT platforms, databases, and field systems - anything - without rip-and-replace. Integrations are designed to support live operational use, automation, and applications, ensuring data flows reliably across systems rather than simply moving data between disconnected tools.
Rayven supports IoT use cases by connecting device and sensor data into a unified operational environment. IoT data is combined with enterprise, operational, and field systems - anything - to drive real-time visibility, automation, and operational applications. This ensures IoT data is used to improve operations, not isolated in monitoring-only platforms.
Rayven enables IoT analytics by combining sensor data with operational context from systems, workflows, and assets - anything. This allows teams to move beyond raw telemetry and dashboards to actionable insights, alerts, and automated responses that directly support operational performance, reliability, and decision-making across distributed environments. Find out more at rayven.io
Rayven is not a traditional low-code development platform used by internal teams to assemble applications themselves. Instead, it delivers fully built, production-ready operational applications on top of a unified data and automation foundation. Customers and partners receive systems designed around their real operational processes, without needing to configure, maintain, or govern low-code tooling internally. This avoids the complexity, risk, and long-term ownership burden typically associated with low-code platforms.
Rayven supports machine learning in a practical, operations-first context. By unifying industrial data from IT, OT, IoT, and field systems, Rayven creates the conditions required for machine learning to work reliably. Models are applied to real operational use cases such as anomaly detection, predictive maintenance, optimisation, and forecasting, and are embedded directly into operational systems rather than existing as standalone data science tools.
Rayven functions as an industrial-focused platform as a service by providing the core data integration, automation, and application foundation needed to deliver complete operational systems. Customers do not need to assemble infrastructure, middleware, or tooling independently. The platform underpins delivered solutions, supporting scalability, security, and extensibility while remaining invisible to end users who simply receive systems that work in real operational environments.
Rayven delivers predictive analytics by combining real-time operational data with automation and intelligence layers that are embedded into day-to-day workflows. This allows teams to anticipate issues such as downtime, delays, capacity constraints, or asset failures and take action early. Predictive insights are contextualised within operational systems, ensuring they drive action rather than existing as isolated forecasts or reports.
Rayven supports preventive maintenance by unifying asset data, condition monitoring, operational history, and live system inputs into a single operational environment. This enables proactive maintenance planning, automated alerts, and data-driven scheduling that reduce unplanned downtime. Preventive maintenance capabilities are integrated into broader operational systems, allowing maintenance teams to work with accurate, current information without replacing existing CMMS or asset systems.
Rayven enables remote monitoring and management across distributed assets, sites, and operations by providing a single, real-time operational view. Teams can monitor asset status, system performance, and operational conditions remotely, detect issues early, and trigger automated or manual actions. This capability integrates data from systems, sensors, and field activity, supporting effective remote oversight without relying on isolated monitoring tools.
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