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AI usage governance: turning scattered model calls into auditable capabilities

When 12 teams call multiple mainstream models independently, how do you satisfy audit, compliance and cost at the same time?

5/15/202612 min readFinance / public sector / manufacturing

AI usage governance: turning scattered model calls into auditable capabilities

Headline

12→1

Department-level calls unified into a governance gateway

A real case from an 8,000-person enterprise: multiple departments wired up mainstream closed-source LLM APIs / private models / domestic open-source models on their own. 18 months in, nobody could say how many calls went out, which data left, or who was paying. This piece walks through how we consolidated it all with one governance gateway.

Billing & quota: put AI cost on the monthly finance sheet

Every capability is billed by token + call count and allocated by department / project / business system. Monthly AI cost reports are auto-generated; the top 10 callers are visible at a glance. At 80% budget usage, an alert fires; at 100%, the gateway degrades to a lower-tier model.

Data classification: customer privacy never leaves the perimeter

The Ouryun gateway has built-in PII detection and redaction — national ID / phone / bank card / customer name are auto-replaced. PII data is forced through the private model; non-PII data is routed by classification to the right region and model. Auditors can export a single record's full flow path in one click.

Audit: every call can be replayed

Full request / response / prompt hash / model version / decision reason are stored. Auditors can filter by user_id / trace_id / capability / time range and export to CSV in one click. A 3-year retention window meets finance and healthcare compliance.

Degradation & fallback: the model must not be a single point of failure

When the primary model is unavailable, the gateway auto-degrades to a private 70B → rule template → human queue. The entire chain is handled transparently by the gateway; business side reads confidence from the capability_status field.

yaml

A policy snippet: route by data class + department budget

# ouryun-gateway policy (English)
capabilities:
  - name: summarize_meeting_note
    owner: crm-team
    sla:
      p95_latency_ms: 1500
      availability: 0.999
    routing:
      primary: primary-cloud-model            # default cloud route
      by_data_class:
        pii: private-llm-70b     # PII forces private deployment
        confidential: regional-cloud-model # confidential goes to the regional cloud
      by_dept_budget:
        marketing: cost-optimized-cloud-model    # marketing cost-down route
        legal: primary-cloud-model             # legal needs higher accuracy
    fallback_chain:
      - private-llm-13b
      - rule-template-v3
      - manual-queue
    audit:
      retention_days: 1095
      log_prompt: false            # prompts not stored (compliance)
      log_response_hash: true