Solution

WHAT PROBLEMS ARE WE SOLVING?

Lack of real-time, granular, and vendor-agnostic visibility

Lack of pattern recognition for high dimensional data

Lack of end-to-end automated controls

How It Works

HOW ARE WE ADDRESSING THE DATA CENTER THERMAL MANAGEMENT PROBLEM?

We solve the problem with a real-time software application that processes chip-level dynamic thermal data for granular, low-latency, and power-efficient cooling controls.

INTRODUCING ADEPTDC SOLUTION

BRINGING RADICAL TRANSPARENCY

Digital Twin for Predictive Risk Management

Digital twin brings real-time, granular, and vendor agnostic visibility into your data center.

Digital Assistant for Continuous Capacity Optimization

Our AI-enabled Digital Assistant maintains optimal capacity utilization for your data center.

Unleash operational clarity

Top Features of Our Software-based Solution

One-click Simplicity

Reduce complex operational tasks related to data center thermal management to a single click and lessen dependence on specialists.

Lightweight

Manage entire thermal stack without additional sensors or agents.

Portable

Manage data center thermal stack consisting any type of hardware.

Fast Time to Value

Deploy and manage a complete solution in minutes.

Computational Efficiency

Capable of handling large heterogeneous dataset.

Robust ML

Minimize data refinement with our robust ML algorithm, capable of handling noisy training data.

Case Study

Real experience

HARDWARE ONBOARDED

better QUALITY

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For the thermal management of a dense and virtualized data center hosting equipment from different vendors, a granular and vendor-agnostic visibility is warranted. With increasingly low-latency IT demand, a real-time visibility is also of importance.
In the absence of an appropriate pattern recognition algorithm, granular and real-time data is just computing burden. To fully utilize it, it is important to be supported by an efficient pattern-recognition algorithm.
Data center thermal management cuts through the entire stack starting from the electronic chip to the building chiller. An coordinated and concurrent operation requires end-to-end automated cooling controls.
This strategy ensures a proper alignment between cooling supply and demand, and provides fine-grained visibility into the thermal health of heterogeneous IT assets. Therefore, we can safely raise IT component temperatures by raising HVAC set points and reduce cooling bills without causing thermal hazards like hot spots.
Enterprise-grade servers supporting AI workloads are at least few orders of magnitude more expensive than the traditional volume servers. The equipment failure cost is too high to be ignored.
Typical lifetime of an IT equipment is 6-18 months, while that for a facilities equipment such as a Liebert cooling systems 15-20 years. The deployment times are also very different. Furthermore, the typical time-scale for data center facilities operations is in order of few minutes, while that for IT systems is few minutes. Therefore, matching data center facilities to its IT demand is very difficult.
Following Moore law’s, the number of transistors in electronic circuit is rapidly increasing at 1.3x annual rate. Moreover, virtualization of computing resources made data center workload rapidly non-uniform. This two factors lead to a complex data center operation.
Data centers are increasingly supporting application ecosystem such as video streaming, high-frequency merchandise, and real-time image recognition. This new generation applications require fast and high-throughput computation.
A typical data center hosts a multitude of IT, power, and cooling systems with varied response characteristics. This makes data center thermal profile non-uniform and complex. In addition to that, turbulent air cooling adds to the data center thermal profile to an extent that it become non-linear. Therefore, it is literally impossible to build a traditional formula-based mathematical modeling for data center thermal evolution. It necessitates a data-driven real-time framework for data center thermal modeling and prediction.
As much as 50% of data center downtimes happen due to thermal issues. AdeptDC’s data-informed predictive maintenance and automated cooling optimization reduces the risks of these downtimes.
Most of the hardware failures occur due to temperature, voltage, power, or humidity related issues. AdetpDC’s solution reduces the hardware mortality rates with its granular and real-time monitoring and end-to-end feedback control solution.
With data center cooling demand being difficult to predict, data center managers are forced to over-compensate their cooling capacity. AdeptDC’s end-to-end automated cooling optimization removes guessworks from the cooling controls, making it more efficient.
Although most of the data center managers are trained IT professionals, a significant part of their work hours are spent on calibrating cooling system and fixing thermal issues. AdeptDC’s predictive maintenance application intends to save time for IT professionals so that they can focus more on their core jobs.
Data center maintenance could be an intractable problem with unpredictable nature of data center operations and complex thermal response patterns. AdeptDC aims to removes this uncertainty and provides data center managers with much needed peace of mind.
More than half of unplanned downtimes are caused by inappropriate operating points (e.g. high temperatures, circuit voltage) and inadequate mitigation procedures (e.g. poor temperature control, response to voltage surge). AdeptDC’s AI solution can efficiently identify the operational weaknesses such as components with high thermal risks and provide early warnings to the operators. It can go an extra  mile by automatically mitigating those weaknesses and preempt expensive downtimes.
The lifetimes of servers and other IT assets get severely affected if they operate beyond a tight operating band. AdeptDC prevents the assets operations outside the band. I also detects equipment operating beyond that band and mitigates the potential damage by dynamic infrastructure optimization.
Most data centers put atleast three times more power capacity than required to meet SLA to handle possible worst case scenarios. AdeptDC’s dynamic thermal management can efficiently handle this problem.
Do you know at least one out of three serves in data centers are comatose, meaning they are just consuming power without performing any useful work? AdeptDC’s AI software offers an efficient and scalable solution.

Monitoring and managing critical thermal data are important for compliance checkup. AdeptDC’s software supports compliance checkup for data centers.

Most data center operators found themselves engaged in low leverage tasks such as sensor deployments, policy configurations, equipment troubleshooting. AdeptDC’s operational intelligence takes care of most these problems.
A data center is deployed with expensive equipment and high-skilled professionals. Striking the best performance point from this heterogeneous resource poor under a time-varying demand profile needs dynamic and granular operational transparency. AdeptDC brings that transparency to the data center operations.
To avoid expensive data center downtimes, data centers deploy redundant capacity. This often leads to stranded capacity causing needlessly high total cost of ownership. AdeptDC’s software reduces these stranded capacity with its superior demand forecasting and scalable deployment.