Astrikos.ai, a leader in AI-driven infrastructure intelligence, is excited to announce the launch of its cutting-edge AI-Powered Data Center Intelligence Platform. This advanced solution is designed to transform data center operations by enabling predictive maintenance, real-time analytics, and enhanced operational efficiency.
Leveraging AI and machine learning, the platform ensures higher uptime, reduced costs, and proactive issue resolution, making it a critical tool for modern data centers. The platform, named S!aP Cognus, brings together machine learning (ML), 3D modeling, and advanced analytics to optimize data center performance. With its scalable architecture, S!aP Cognus is capable of monitoring thousands of devices while providing predictive insights and real-time visibility into the most critical aspects of data center management.
Key Features of the Platform:
- AI-Powered Predictive Maintenance: Utilizes machine learning models to predict failures in vital systems such as UPS, HVAC, and battery banks, significantly reducing unplanned outages.
- KPI Engine Compliant with ISO/IEC Standards: Tracks energy efficiency and operational performance according to recognized benchmarks like Power Usage Effectiveness (PUE), Water Usage Effectiveness (WUE), and Energy Reuse Effectiveness (ERE), aligning with global sustainability and compliance mandates.
- Real-Time 3D Visualizations: Offers a dynamic digital twin of data centers, helping operators identify issues, simulate potential failures, and monitor live conditions.
- Modular & OEM-Agnostic Architecture: Supports a wide range of protocols (e.g., Modbus, SNMP, BACnet) and integrates with popular hardware from Schneider, Siemens, APC, and others, reducing deployment friction.
- Role-Based Dashboards: Delivers tailored dashboards for various stakeholders including Data Center Managers, Sustainability Officers, and Finance Teams to support informed decision-making.
- Low-Code ML Model Builder: Provides an intuitive interface to design and deploy custom Machine Learning models for specific data center needs without requiring advanced coding expertise.
“With the exponential growth of data and cloud infrastructure, enterprises need intelligent, AI-driven platforms that go beyond traditional monitoring,” said Chinmay Hegde, CEO & Managing Director of Astrikos.ai. “Our new Data Center Intelligence Platform empowers operators with real-time insights, predictive analytics, and automation to significantly improve efficiency, reduce downtime, and enhance overall sustainability.“
Chandrashekar SK, CTO of Astrikos.ai, added, “Traditional data center management is reactive, leading to inefficiencies and unexpected failures. S!aP brings a proactive approach, enabling AI-powered predictive maintenance, interactive 3D modeling, and seamless third-party integrations to transform how data centers operate in the digital age.”
Astrikos.ai’s S!aP Cognus platform is designed to deliver energy efficiency, reliability, and sustainability in data center operations. By leveraging AI and machine learning, the platform enables trend analysis, scenario planning, and infrastructure optimization, facilitating strategic decisions that enhance operational agility and resilience.
The S!aP platform has already been implemented successfully across several high-profile projects, including Uttar Pradesh’s UP 112, the world’s largest Next-Gen Emergency Response Support System (ERSS). The platform also played a pivotal role in the 2025 Prayagraj Kumbh Mela, supporting critical emergency response efforts. And also, 29+ pilot projects which includes 10+ smart cities, 3 data centers across 4 geographies.
“With the increasing demands on data centers to deliver continuous uptime and meet sustainability goals, S!aP Cognus is a game-changer,” said Suresh Bulusu, Director of Sales of Astrikos.ai. “This platform not only provides predictive insights and operational intelligence but also empowers our clients with actionable data that drives smarter decisions, lower costs, and enhanced performance across their data center ecosystems.”
The platform represents a significant advancement in intelligent infrastructure management, contributing to energy savings and sustainability goals while ensuring operational resilience through AI-driven analytics.
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