LogiqPulse inspects inference latency, semantic drift, and token burn across multi-model deployments—before your monthly cloud invoice arrives.
Anthropic · OpenAI · AWS Bedrock · Vertex AI · OpenTelemetry-native
p99 latency
312ms
−18ms vs 1h · p50 118ms
Token burn
$41.12/hr
proj. $29.6k / 30d
Cache hit rate
84.2%
+6.1 pts vs 24h
Throughput
1,284 req/s
429 rate 0.26%
Request throughput by model
req/s · 10s buckets
01 — Capabilities
The collector runs as a sidecar or SDK middleware, captures every request at the token level, and ships spans over OTLP. No proxy rewrites, no prompt payloads leaving your VPC unless you opt in.
Pinpoint un-cached system prompts degrading latency across Anthropic endpoints. Each prompt prefix is fingerprinted so you can see which templates miss cache_control breakpoints and what they cost in TTFT.
Catch hallucinated JSON responses and malformed payloads without human review. Responses are validated against your declared schemas and scored against a rolling embedding baseline per route.
Auto-route traffic to secondary providers when primary inference limits trip 429 status codes. Policies honor retry-after, per-tenant budgets, and model-equivalence maps you define.
4.2B+
tokens tracked daily
<1.8ms
pipeline overhead, p99
99.99%
gateway uptime, trailing 12 mo
SOC 2
Type II certified · report under NDA
02 — Early access
Early testers receive $1,000 in credits applied to span ingest and 30-day retention. We review requests within one business day and prioritize teams running more than one model provider in production.