# AI observability — Use case > Real-time telemetry for every prompt, completion, agent call, and tool invocation. Latency, cost, quality, drift — joined to the same audit ledger as API traffic. *AI teams · Telemetry · For AI teams* ## See every prompt. Trace every chain. Catch every drift. Apinizer's AI lane joins prompts, completions, MCP calls, and A2A conversations into one Elasticsearch index — and one audit ledger. Quality drift, cost spikes, and latency tail all live on the same dashboards. [Request a demo](https://calendly.com/apinizer/15min) · [Read the docs](https://apinizer.com/developers/docs) --- ## The problem *The problem* ### AI observability is usually a notebook on someone's laptop. The model team has a spreadsheet of prompt samples. The platform team has Prometheus. Compliance has nothing. When 'quality drops on Tuesdays' becomes a question, three tools disagree. Apinizer puts every AI event — prompt, completion, tool call, agent conversation — in one place, alongside cost and audit. The Tuesday question becomes one query. --- ## Capabilities ### Per-call telemetry Prompt fingerprint, completion fingerprint, latency, tokens, cost, model, consumer, route decision — captured per call. ### Quality and drift sampling Configurable sampling on completions for offline review. Drift detection on output distribution — when 'summarize' starts answering longer, the alarm fires. ### Cost + latency + quality on one view The three numbers every AI decision balances — one dashboard, joined by call, broken out by intent. ### Forensic chains Reconstruct any agent chain end-to-end — including MCP invocations and A2A hops. The query joins prompts to tool calls to completions to user-facing responses. ### Anomaly + severity-aware alarms EMA + Bollinger bands on AI metrics. P1 to on-call when latency tail blows; P3 to digest when miss rate creeps. ### Joins to the audit ledger Every AI event sits alongside the audit ledger. Regulator questions about AI decisions resolve as a saved query, not a forensic project. --- ## Real-world examples ### Banking **Scenario:** Istanbul bank traces a contested chatbot answer to the exact prompt **Outcome:** Customer complaint cited a specific answer; audit query returned the prompt, model, route decision, and tool calls in seconds. Response: one paragraph, end of week. ### Insurance **Scenario:** Munich insurer catches a quiet quality drift on a Tuesday morning **Outcome:** Completion-length distribution shifted right by 18%. Drift alarm fired; team paused traffic, rolled back the system prompt, returned to baseline. **Metric:** Drift caught in <30 min ### Public sector **Scenario:** Paris agency proves an AI decision did not depend on personal data **Outcome:** Audit query: 'what context entered the model for this citizen's case'. Result: no PII; the redaction firewall did its job. Complaint closed with evidence. ### Telecom **Scenario:** Madrid carrier joins prompt cost to support-ticket NPS **Outcome:** Tickets resolved by AI tagged with their prompt cost; cost per NPS point computed. Finance sees the unit economics in their own dashboard. ### Media **Scenario:** Milan publisher samples 1% of completions for quality review **Outcome:** Quality reviewers pull samples from the gateway, score them in-platform, feed scores back into routing policy. The feedback loop is one click. ### Retail **Scenario:** Amsterdam marketplace reconstructs an agent chain after a partner complaint **Outcome:** The chain hit MCP → A2A → MCP → API. The audit query returned each leg in order; root cause posted to the partner within a day. ### Healthcare **Scenario:** Prague hospital alarms on latency tail in clinical chatbot **Outcome:** P99 latency drifted from 2.4s to 3.9s overnight. Anomaly alarm fired; root cause was a provider degradation; routing rolled to secondary in 90 seconds. ### Energy **Scenario:** Baku utility separates ops-agent telemetry from analytics-agent telemetry **Outcome:** Operations have stricter alarms; analytics have looser ones. Same observability surface, different policies per agent class. --- ## Recommended modules - [AI Gateway](https://apinizer.com/products/ai-gateway) — Per-call telemetry, quality sampling, drift detection, chain reconstruction. - [Analytics Engine](https://apinizer.com/products/analytics-engine) — Elasticsearch-backed dashboards for cost, latency, quality, and audit on one view. - [Monitoring](https://apinizer.com/products/monitoring) — Anomaly detection on AI metrics; severity-aware alarms wired to your on-call. - [API Gateway](https://apinizer.com/products/api-gateway) — AI traffic and API traffic in one observability plane — joined by consumer and audit. --- ## Resources - [AI observability overview](https://docs.apinizer.com/en) — Per-call telemetry, quality sampling, drift detection, forensic chains. - [AI Gateway](https://apinizer.com/products/ai-gateway) — Where every AI event lands — alongside routing, caching, firewalls. - [Analytics Engine](https://apinizer.com/products/analytics-engine) — Cost, latency, quality, and audit on one Elasticsearch. - [Monitoring](https://apinizer.com/products/monitoring) — Anomaly detection and severity-aware action chains. - [Compliance lane](https://apinizer.com/solutions/kvkk-gdpr-bddk-compliance) — How AI observability feeds KVKK / GDPR / BDDK evidence. - [Architecture overview](https://docs.apinizer.com/en/concepts/architecture) — Where AI telemetry sits in the platform. --- ## Related use cases - [Observability & audit](https://apinizer.com/solutions/observability-audit) — For platform teams - [Token economics](https://apinizer.com/solutions/token-economics) — For AI teams - [Prompt firewalls](https://apinizer.com/solutions/prompt-firewalls) — For AI teams - [Agent-to-Agent (A2A)](https://apinizer.com/solutions/agent-to-agent) — For AI teams --- ## Next step *AI observability, joined* **Every prompt. Every chain. Every alarm.** A 30-minute walkthrough — telemetry, drift, alarms, audit — on a Kubernetes of your choice. [Book a Demo](https://calendly.com/apinizer/15min) · [Read the docs](https://apinizer.com/developers/docs) --- ## Links - Products: https://apinizer.com/products - AI Gateway: https://apinizer.com/products/ai-gateway - Solutions: https://apinizer.com/solutions - Pricing: https://apinizer.com/pricing - Developers: https://apinizer.com/developers - Documentation: https://docs.apinizer.com/index-en - Blog: https://apinizer.com/blog - Contact: https://apinizer.com/company/contact © 2026 Apinizer. All rights reserved.