How teams build with Deep Variance
Five industry verticals running infrastructure at scale. Real problems, measured outcomes, no generic cloud pitch.
Training and inference at scale
Long-running GPU workloads — from multi-week training jobs to high-throughput LLM inference — waste energy and compute. DeepTuner and Optimemory optimize power, memory, and throughput without changing your code.
−50%
Energy per token
Turn idle GPU capacity into revenue
Customers over-provision GPUs to avoid out-of-memory errors, leaving capacity stranded. Optimemory unlocks that capacity automatically.
+38%
Fleet utilization
On-premise ML for regulated industries
Financial, healthcare, and insurance firms need on-premise infrastructure that stays efficient across long training runs and strict compliance requirements.
11w → 3d
Development cycle
Train larger models on limited research budgets
Research labs hit memory limits before they can test their hypotheses. Optimemory doubles the model size you can train on existing hardware.
3B → 6B
Model scale
Real-time AI quality control at the edge
Vision models for quality inspection must run on factory-floor hardware with no cloud latency and no data leaving the facility.
1.5x
Faster inference
Recognize your infrastructure problem?
We scope every deployment to your hardware, data governance constraints, and team size. No generic pricing tiers, just what fits.