AI Workload Optimization
Automatically adjust AI resources in real-time to maximizes efficiency
Understanding AI workloads
AI workloads often fluctuate in their demands. Choosing the right resource configuration manually requires a deep understanding of workload characteristics that often aren't known ahead of time, especially for dynamic or new workloads.
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Historical data: traffic peaks daily at 12pm (+280% avg)
Predicted +310% volume in ~8 min · confidence 91%
Vector store · Memory layer · Tool compute ready
haiku-4 → sonnet-4 (65% of traffic) — ahead of peak
Traffic +298% · Budget utilisation 71% · p95 1420ms
Autoscaling variable AI workloads
Unomiq dynamically profiles each AI workload holistically and can adjust resource allocation in real time, so your entire agent stack stays efficient as demand evolves.
Dynamic resource configuration
AI workloads that run efficiently at low volume may over-provision at peak and waste spend — or under-provision and miss SLAs. Unomiq gets the balance right by continuously adjusting thresholds based on real observed patterns, so your AI workloads stay efficient as demand changes — without anyone watching dashboards or rewriting configs.
Fixed high capacity — wastes spend during off-peak hours
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