Every AI call records Token/duration/status/tool calls. Three-layer logs record different level information.

From user input to final output, every step is completely recorded for true full-chain traceability.

1)    AI audit log: records agent call info including agent name, user, time, status.

2)    LLM call log: records LLM call info including provider, model, token consumption, response time.

3)    Tool call log: records tool call info including tool name, input params, output results, execution time.

4)    Log correlation: three layers correlated by call chain ID, traceable from any layer to others.

Budgets by agent/project/department, alerts on overflow, budget and alert separation.

Fine-grained cost control, not just total cost but per-dimension cost.

1)    Multi-dimensional budgets: budgets by agent, project, department for multi-dimensional control.

2)    Real-time monitoring: real-time cost consumption monitoring, comparing with budgets.

3)    Alert notifications: auto-alerts on overflow, supporting email and message notifications.

4)    Budget-alert separation: budget settings and alert rules managed separately for flexibility.

Auto-mask sensitive data before AI calls, audit logs don't leak sensitive info.

Data masking pipeline auto-identifies and masks sensitive data before AI calls.

1)    Auto-identification: auto-identifies sensitive data including phone, ID, bank card numbers.

2)    Masking rules: configurable masking rules supporting partial, full, replacement modes.

3)    Audit safety: sensitive data in audit logs auto-masked, no leakage.

4)    Compliance: meets GDPR, personal information protection law requirements.

Auto-alert on Token limit/response timeout/exception, configurable rules.

Flexible alert mechanism with configurable conditions, levels, and notifications.

1)    Token limit alert: auto-alert when token consumption exceeds threshold.

2)    Response timeout alert: auto-alert when AI response time exceeds threshold.

3)    Exception alert: auto-alert on AI execution exceptions including LLM and tool errors.

4)    Configurable rules: alert conditions, levels, notification methods all configurable.

Measurable values plus coefficients plus calculation services plus audit logs for precise AI value measurement.

Not simple token-based billing, but billing based on AI-delivered business value.

1)    Measurable values: define measurable business value indicators like orders processed, reports generated.

2)    Coefficients: set coefficients for different value indicators reflecting business value weight.

3)    Calculation services: calculate AI-delivered value based on measurable values and coefficients.

4)    Audit logs: complete audit logs for billing process ensuring traceability.

AI call costs allocated by project, quantifying each project's AI resource consumption.

Fine-grained cost allocation helping managers understand each project's AI ROI.

1)    Project dimension allocation: AI call costs allocated by project, quantifying consumption.

2)    Cost analysis: multi-dimensional cost analysis reports by time, project, agent dimensions.

3)    ROI analysis: calculate each project's AI ROI combining business value indicators.