Engineering Control Plane for AI Infrastructure
XARIV helps engineering teams reduce the time, cost, and uncertainty of building AI systems — from first workload sketch to procurement-ready architecture review.
The v1 experience every engineer can finish today — no account required.
Sizing, latency percentiles, utilization, and eco impact in one view.
Start →Bottleneck classification with ranked optimization actions.
Start →Includes optional calculators (step 0) before the core platform workflow.
Quick check
Is this workload in the right ballpark?
Optional first pass with free calculators — KV cache, GPU memory, cost, throughput, carbon. Under 30 seconds each before you commit to a full analysis.
Define
Which model, hardware, and traffic shape?
Open Lens and define your AI workload — model, GPU, context length, QPS, batch size, and p99 SLO. This is the foundation every downstream decision builds on.
Benchmark
Does this stack hit SLO on actual request patterns?
Run Pulse on ShareGPT, LMSYS, or custom prompts. Collect TTFT, ITL, TPOT, throughput, and GPU telemetry — the evidence layer for your decision.
Analyze
What's the bottleneck and what should we change?
Lens explains the binding constraint — memory, compute, or network — with ranked recommendations. Pulse validates whether the fix holds under real traffic.
Decide
Why this GPU count, this cost, this carbon footprint?
Package sizing, latency evidence, cost economics, and eco metrics into a report your team can approve — engineering, FinOps, and leadership on the same page.
Step 3 · Analyze
Lens provides sizing, cost, bottleneck classification, and ranked recommendations. Pulse adds latency percentiles and GPU telemetry. Together they form the evidence layer for your architecture decision — the report your team approves before procurement.
Provisioned 31 GPUs instead of 48 — 35% capex reduction with SLO met on day one.
Start at Define
Set user growth and workload targets
Start at Benchmark
Compare models and latency profiles
Start at Define
GPU sizing and architecture
Start at Benchmark
Validate p99 SLO before cutover
Start at Decide
Monthly GPU bill and cost per request
Start at Decide
Approve deployment with evidence
Today — fragmented
Nobody owns the entire engineering decision workflow.
With XARIV — one platform