An autonomous engine that deploys intelligent AI agents to continuously observe, learn, and optimize your block storage infrastructure in real-time without any app changes or downtime, saving significant DevOps and SRE efforts.
Self-driving storage agents that rights-size volumes automatically without human intervention.
ML models analyze usage patterns to forecast spikes and provision capacity before it's needed.
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Define and enforce custom guardrails for budget, performance, and compliance across your fleet.
Production-ready on AWS today, with unified support for Azure and GCP coming soon.
An autonomous engine that deploys intelligent AI agents to continuously observe, learn, and optimize your block storage infrastructure in real-time without any app changes or downtime, saving significant DevOps and SRE efforts.
Cost Reduction
Downtime
Auditability
App changes
Self-driving storage agents that rights-size volumes automatically without human intervention.
ML models analyze usage patterns to forecast spikes and provision capacity before it's needed.
Define and enforce custom guardrails for budget, performance, and compliance across your fleet.
Production-ready on AWS today, with unified support for Azure and GCP coming soon.
Cost Reduction
Downtime
Auditability
App changes
Self-driving storage agents that rights-size volumes automatically without human intervention.
ML models analyze usage patterns to forecast spikes and provision capacity before it's needed.
Define and enforce custom guardrails for budget, performance, and compliance across your fleet.
Production-ready on AWS today, with unified support for Azure and GCP coming soon.
Cost Reduction
Downtime
Auditability
App changes
Self-driving storage agents that rights-size volumes automatically without human intervention.
ML models analyze usage patterns to forecast spikes and provision capacity before it's needed.
Define and enforce custom guardrails for budget, performance, and compliance across your fleet.
Production-ready on AWS today, with unified support for Azure and GCP coming soon.
Skyriq's AI engine forecasts capacity in advance and proactively adjusts storage to prevent disk failure, over-allocation, and idle resources.
Skyriq's AI engine forecasts capacity needs 24 hours in advance, proactively adjusting storage to prevent spikes while eliminating idle resources.
Prediction Accuracy
High-fidelity forecasting using ML models minimizes buffer requirements
Look-ahead Window
Continuous rolling forecast for proactive management
Optimization Frequency
Micro-adjustments every minute to match demand
Prediction Accuracy
High-fidelity forecasting using ML models minimizes buffer requirements
Look-ahead Window
Continuous rolling forecast for proactive management
Optimization Frequency
Micro-adjustments every minute to match demand
Skyriq runs a closed-loop system that continuously observes, learns, decides, and acts with minimal human involvement.
Skyriq runs a closed-loop system that continuously observes, learns, decides, and acts with minimal human involvement.
Automatically discovers new storage nodes, volumes, and workloads across AWS, Azure, and GCP without manual configuration.
Continuously measures capacity, IOPS, throughput, and utilization to understand unique workload patterns and growth trends.
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Executes precise scale-up or shrink-down operations in real-time, enforcing policies with zero downtime or app changes.
Determines optimal capacity using ML models, identifying performance risks and cost tradeoffs before taking action.
Skyriq runs a closed-loop system that continuously observes, leaarns, decides, and acts with minumal human involvement.
Skyriq runs a closed-loop system that continuously observes, learns, decides, and acts with minimal human involvement.
Automatically discovers new storage nodes, volumes, and workloads across AWS, Azure, and GCP without manual configuration.
Continuously measures capacity, IOPS, throughput, and utilization to understand unique workload patterns and growth trends.
Determines optimal capacity using ML models, identifying performance risks and cost tradeoffs before taking action.
Executes precise scale-up or shrink-down operations in real-time, enforcing policies with zero downtime or app changes.
Skyriq runs a closed-loop system that continuously observes, learns, decides, and acts with minimal human involvement.
Skyriq runs a closed-loop system that continuously observes, learns, decides, and acts with minimal human involvement.
Automatically discovers new storage nodes, volumes, and workloads across AWS, Azure, and GCP without manual configuration.
Continuously measures capacity, IOPS, throughput, and utilization to understand unique workload patterns and growth trends.
Executes precise scale-up or shrink-down operations in real-time, enforcing policies with zero downtime or app changes.
Determines optimal capacity using ML models, identifying performance risks and cost tradeoffs before taking action.
Skyriq runs a closed-loop system that continuously observes, learns, decides, and acts with minimal human involvement.
A multi-agent autonomous system where specialized AI agents collaborate to observe, reason, and execute storage optimization in real-time.
Scan & identify resources
Collect real-time metrics
Guardrails & Compliance
Decision logic & Trade-offs
ML Forecasting
Autonomous execution of sizing operations
Autonomous execution of sizing operations
A multi-agent autonomous system where specialized AI agents collaborate to observe, reason, and execute storage optimization in real-time
A multi-agent autonomous system where specialized AI agents collaborate to observe, reason, and execute storage optimization in real-time.
Scan & identify resources
Collect real-time metrics
Scan & identify resources
Collect real-time metrics
Guardrails & Compliance
Decision logic & Trade-offs
ML Forecasting
Guardrails & Compliance
Decision logic & Trade-offs
ML Forecasting
Autonomous execution of sizing operations
Autonomous execution of sizing operations
Autonomous execution of sizing operations
Autonomous execution of sizing operations
Skyriq runs a closed-loop system that continuously observes, learns, decides, and acts with minimal human involvement.
A multi-agent autonomous system where specialized AI agents collaborate to observe, reason, and execute storage optimization in real-time.
Scan & identify resources
Collect real-time metrics
Guardrails & Compliance
Decision logic & Trade-offs
ML Forecasting
Autonomous execution of sizing operations
Autonomous execution of sizing operations
Why Skyriq stands apart from traditional and cloud-native storage solutions.
Why Skyriq stands apart from traditional and cloud-native storage soltions.
Why Skyriq stands apart from traditional and cloud-native storage solutions.
Why Skyriq stands apart from traditional and cloud-native storage solutions.