data-analysis

Weekly or monthly cost review when you want to understand spending by model and identify high-cost sessions for optimization.

Route agent calls to cheapest/fastest available LLM model dynamically based on live pricing and failure signals.

Agent development where you need quantified evidence of loop quality improvement—when optimizing stuck detection, reflection patterns, or escalation thresholds.

Individual contributor or team lead reviewing personal/team productivity—weekly check-in on what worked and what to optimize.

Real-time cost visibility and burn-down forecasting for multi-agent runs.

Weekly review of what's actually happening in your system — peak usage patterns, which tools are most relied on, error spikes.

Monthly review of system health and team performance when you want a single 0-100 number with component breakdown and trend comparison.

Tracking spending across parallel agentic runs to catch token leaks

Debugging AgentCore agent sessions, tracing tool calls, or analyzing latency