The goal is to democratize IIoT data analytics by using natural language queries instead of coding or specialized tools. Current Method (MCP Baseline): Cumulocity allows simple device interaction via natural language (e.g., "What's the status of Turbine 4?"). Deeper, insight-driven analytics requires exporting data, using external tools, or custom scripting. ResEt AI's SIA Solution: The Agentic AI Layer via SIA (Suite of Intelligent Agents) enables complex, insight-driven analytics through the same conversational interface. Users can ask questions like: "Analyze the last 90 days of vibration data and identify early signs of failure". SIA's Fusion Engine delivers high accuracy with regression-level explainability (Transparent AI). Joint Value: This capability empowers any user to instantly extract insights from data just by asking questions in their preferred language. It eliminates the need for coding or data science expertise for complex analysis. This results in faster time-to-insight and unlocks growth by allowing domain experts to use the AI-first Decision platform to query multi-source, layered data.
- Technology Partner
- Energy & Utilities
- Healthcare & Medical
- Industrial & Manufacturing
- Transportation & Logistics
- Warehouse & Facilities
- Asia Pacific
- Europe
- Middle East
- Machine Learning & AI
- Predictive Maintenance
Agentic AI-Enabled Decision Intelligence for OEMs, Utilities and Industrial Manufacturers. Leveraging data from connected devices to drive business growth and make smarter decision. No Code, No Integration, No Data Science background required.
ResEt AI’s platform SIA (Suite of Intelligent Agents) helps customers extract value from their existing unstructured and structured data including times series data without requiring coding or data science teams. Customers don't have to waste time and money on rigid integrations or change management. Get started on day one.
SIA combines machine learning and explainable AI to analyze telemetry, operational, process, and business datasets, converting unstructured data (PDFs, logs, reports) into structured intelligence and delivering clear, actionable recommendations across areas like throughput improvement, energy optimization, quality control, inventory planning, and procurement analytics.
For Cumulocity customers, SIA acts as an agentic intelligence layer on top of connected-device data. It extends Cumulocity’s device and asset connectivity with decision-ready intelligence, translating IoT telemetry into actionable business recommendations that improve efficiency, yield, and cost using the existing Cumulocity ecosystem.
Cumulocity and ResEt AI Solutions Pvt. Ltd.
About ResEt AI
ResEt AI is a Bengaluru-headquartered company pioneering agentic AI for industrial decision intelligence. Its flagship platform, SIA (Suite of Intelligent Agents), empowers OEMs, utilities, and manufacturing enterprises to extract value from structured, unstructured, and time-series data without coding, integrations, or data-science teams.
Built on proprietary IP that fuses regression-level explainability with neural-network-grade performance, SIA delivers transparent, high-accuracy, data backed recommendations that business users can trust and act upon.
Under the hood, a complex web of AI Agents work in tandem to handle complex tasks ranging from data extraction to preparation, to ML model creation to recommendation, helping teams achieve measurable gains in throughput, energy efficiency, cost reduction, forecasting and planning.
ResEt AI serves global clients across India, Europe, and the Middle East.
ResEt AI × Cumulocity
Together, Cumulocity and ResEt AI bring the power of connectivity and Agentic AI driven intelligence into one seamless ecosystem.
Cumulocity provides a robust foundation for secure device connectivity, & telemetry data. ResEt AI builds on this layer by adding Agentic AI-driven decision intelligence that interprets connected-device data to uncover root causes, predict inefficiencies, and simulate corrective actions before they impact performance.
Through this partnership, Cumulocity users can augment their learnings and operations with no-code, explainable AI agents that deliver recommendations in context that their teams can understand. Optimizing production, energy, quality, or maintenance, all can be achieved in your teams preferred regional language
The result is an integrated AIoT environment where devices think, reason, and recommend, enabling customers to move from monitoring operations to driving strategic, data-backed growth.
Use Cases
This use case allows users to effortlessly detect trends, anomalies, and failure indicators from historical telemetry without requiring scripting or model development. Current Method (MCP Baseline): Users must export time series data, use external tools, or involve data science teams to develop specialized models. This manual process is slow, expensive, and creates a backlog of analytical needs, delaying predictive maintenance. ResEt AI's SIA Solution: The AI (ML Agent and Data Prep Agent ) directly explores Cumulocity's historical data and surfaces insights autonomously. Users can ask sophisticated questions like: "Detect any recurring patterns in wind speed and blade pitch that precede a drop in power generation". This is a No-Code solution , powered by SIA's Fusion Engine, making advanced time series analysis accessible to domain experts. Joint Value: Unlocks deep historical analysis and predictive maintenance insights instantly, without requiring custom code or building specialized models. The system automatically explores data and surfaces key insights, enabling proactive decision-making.
This focuses on allowing users to simulate hypothetical operational scenarios and explore potential outcomes instantly, using natural language. Current Method (MCP Baseline): Scenario simulation requires custom model development, custom simulations, and significant domain expertise. It is not an on-demand, interactive process, limiting proactive planning. ResEt AI's SIA Solution: The What-if Agent instantly runs simulations using internal knowledge and live or historical data. Users can simply ask: “What if wind speed increases by 20% — how will it affect energy output?” or “Simulate the stress on blades during a heavy storm scenario”. The entire simulation process is performed through natural language , leveraging the Fusion Engine's high performance and explainability. Joint Value: Transforms raw IoT data into an interactive, no-code simulation environment. It allows operational teams to instantly model complex, hypothetical scenarios to assess risk and explore optimization strategies, speeding up planning and decision support.