AI Model Observability Architecture Generator

Instrument LLMs and ML models with tracing, metrics, drift detection, and user feedback

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Frequently Asked Questions

Common questions about ai model observability architecture generator

What should I log?▼

Prompts, model versions, retrieval context, tool calls, responses, latency, cost, and user feedback with PII controls.

How do I detect drift?▼

Track feature distributions and output changes over time. Alert on significant shifts and degraded metrics.

How do I trace LLM calls?▼

Propagate trace IDs through routers, retrieval, tools, and model calls. Visualize spans for latency hotspots.

How do I collect feedback?▼

Add thumbs up/down, reasons, and freeform comments. Store for evaluation and fine-tuning pipelines.

How do I govern access?▼

Restrict sensitive logs, redact PII, and enforce retention limits. Provide tenant-isolated dashboards.

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