LLM OBSERVABILITY

Understand model behavior before it becomes operational risk

AnoSys monitors prompts, completions, parameters, latency, token spend, eval scores, safety checks, and downstream business outcomes across every LLM workflow.
LatencyToken costQualitySafety
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Model Analytics
Cost and PerformanceModel behavior tied to latency, tokens, quality, and business outcomes
p95 drift
$0.42per active hour
+38%token spend
842mstool latency
94.2%eval score
Pain

Model metrics without context do not explain failures

A latency spike, cost jump, or quality drop only matters when you know the prompt, model, tool, customer, workflow, and outcome it affected.

AnoSys Answer

Connect model behavior to operations

AnoSys ties model calls to traces, evals, token cost, users, teams, business processes, dashboards, alerts, and AI-assisted root cause analysis.

Use LLM observability to answer the hard questions
01

What changed?

Track model versions, parameters, prompts, tools, providers, and release changes.

02

What did it cost?

Attribute token and model spend to teams, users, agents, workflows, and outcomes.

03

Was it good?

Connect model behavior to evals, AutoJudge scores, safety checks, and quality trends.

04

Who is affected?

Join model telemetry with customer experience, business KPIs, and process health.

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