Included in ZOLIX Advance

AI FinOps

Deep operational tuning for your running AI workloads. ZOLIX AI FinOps monitors your GPU VRAM utilization in real-time, identifying hoarding behaviors and recommending precise rightsizing to ensure maximum ROI.

Right AI Model

GPT, Llama, Claude

Right Infrastructure

H100, A100, L4 GPUs

Perfect AI FinOps

Optimization

VRAM Tracking

Stop paying for idle memory. We track VRAM usage during inference to recommend exact batch sizes and model quantization techniques (e.g., INT8/FP4).

Efficiency

Token Caching

Monitor prompt caching efficiency. The C2O Engine identifies repetitive queries and recommends semantic caching layers to bypass expensive LLM generation entirely.

Pipeline

Context Window Waste

Identify bloated RAG pipelines. ZOLIX analyzes retrieved context relevance to ensure you aren't stuffing 100k tokens into a prompt when 10k would suffice.

Routing

Dynamic Model Routing

Automatically route simple queries to cheaper models (e.g., Llama 3 8B) and complex reasoning tasks to premium models (e.g., GPT-4), saving up to 80% on API costs.

Continuous AI Optimization

AI models are dynamic, and so are their costs. AI FinOps continuously monitors your production workloads to ensure you aren't overpaying for inference or training.

Real-Time Metrics

Monitor GPU core utilization, VRAM allocation, and PCIe bandwidth in real-time to identify bottlenecks and idle instances immediately.

Vector DB Tuning

Optimize your Pinecone, Milvus, or Weaviate clusters. We recommend the perfect balance of memory-optimized vs. storage-optimized nodes based on your retrieval latency.

Multi-Tenant Slicing

Maximize hardware ROI by implementing Multi-Instance GPU (MIG) slicing, allowing multiple smaller models to share a single A100 or H100 securely.

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