Lucend offers an AI‑powered analytics platform that continuously ingests sensor data from BMS, DCIM, and SCADA systems in data centers. It generates daily briefings that identify inefficiencies, predict equipment anomalies, and provide prescriptive maintenance actions with quantified ROI forecasts, automatically populating ITSM tickets and MOP documents. The solution runs on existing sensor infrastructure, delivering cost and PUE improvements without additional hardware investment.
Funding
Funding not disclosed
Founders
Product
Problem
Data center operators receive millions of sensor readings daily—temperature, fan speeds, power draws, humidity—but the critical patterns indicating inefficiencies or emerging failures are buried in this noise. Without tools to surface these signals, facilities spend time firefighting, incur high Power Usage Effectiveness (PUE), and miss cost‑saving opportunities.
Solution
Lucend applies a Transparent AI analytics engine to existing BMS, DCIM, or SCADA sensor streams, continuously detecting hidden inefficiencies and early‑stage hardware anomalies. Each morning the platform delivers a concise intelligence briefing that includes a diagnosed symptom, a data‑backed explanation, and a projected impact for each recommended action. Recommendations are prescriptive, optional, and tied to verifiable data trails so operators can audit the insight generation process. The solution integrates with common ITSM tools such as ServiceNow, auto‑populating maintenance‑of‑procedure (MOP) documents and feeding ROI metrics into existing dashboards. Because Lucend leverages only the sensors already deployed, there is no additional capital expenditure or hardware rollout. The platform’s ROI dashboard tracks projected versus actual savings, enabling facilities to demonstrate cost reductions to leadership. Deployment typically reaches actionable recommendations within six weeks, with minimal training required.
Target Audience
Primary customers are data center operators and facilities engineering teams responsible for performance, reliability, and sustainability, as well as ESG leaders seeking measurable efficiency metrics.
Features
- Transparent AI engine that ingests and correlates millions of sensor data points in real time to surface hidden patterns
- Daily intelligence briefing delivering symptom identification, diagnostic data trail, and impact‑forecasted recommendation
- Seamless integration with BMS, DCIM, SCADA, and ITSM platforms (e.g., ServiceNow) for automated MOP generation and ticketing
- Predictive anomaly detection module that flags equipment health issues before they cause outages
- Prescriptive maintenance guidance calibrated to each asset’s usage profile, with quantified ROI projections
- No‑hardware‑addition architecture: operates entirely on existing sensor infrastructure, eliminating CapEx
- ROI and efficiency dashboard that logs projected savings, actual PUE improvements, and water‑use reductions for auditability
- Rapid onboarding workflow: one‑hour training, system connection in week 1, actionable insights by week 6