Review usage and AI settings

Open Settings → Account for the current plan and usage period. Teml shows pooled events with a logs, spans, product-events, and errors breakdown; active metric series; replay sessions; and the organization’s retention window.

Interpret usage states

The dashboard warns at 80% of a limit and shows a degraded state at 100%. The meter may take a few minutes to appear for a new organization. It is an organization-wide monthly view, so changing the selected project does not make the total project-only.

When approaching a limit, first remove accidental high-cardinality metrics, noisy debug logs, or unnecessary replay capture. Do not reduce error capture before low-value volume.

The active agreement and Plan & Usage card are authoritative for an organization. Public pricing tables describe planned self-serve tiers and may differ during early access.

Set LLM pricing overrides

Open Settings → AI → LLM Pricing Overrides when a model’s organization-specific input, output, or cache token price differs from Teml’s built-in catalog. Rates are stored as USD per token.

Use the exact model identifier emitted by instrumentation. After saving an override, inspect a new model call in Agent Runs or Traces → LLM Costs; historic values may not be recomputed.

Configure automatic quality checks

Open Settings → AI → Automatic Quality Checks to control sampled LLM-as-judge evaluation of agent runs. Start with a small sample, choose only criteria the recorded run contains enough evidence to judge, and review results before increasing coverage. Automated scores are investigation signals, not proof of correctness.

• Plans, limits, and retention
• Explain LLM spend per customer
• Investigate agent runs