AI · Governance

AI policies

Thresholds, routing, escalation, model selection · last updated by Sam Hagen on 2026-05-02

Active policies

24

across thresholds, routing, escalation, models

Confidence threshold

Medium · 0.70

global default · per-policy overrides allowed

Auto-escalations

8

per week · trailing avg

Models in use

4

Opus 4.7 · Sonnet 4.6 · Sonnet 4.6 (vision) · Haiku 4.5

Recommended adjustments
AI-flagged · producers decide
  • Risk flag confidence at 0.70 is producing 23% false positives this month — consider raising to 0.75.
  • Brief auto-categorization confidence threshold of 0.65 means 1 in 8 intakes still goes to human review — within target.

AI grounded in last 30 days of policy outcomes

Model assignment per task

Each AI workflow has a primary and (optional) fallback model

10 tasks
TaskPrimary modelFallbackNotes
Brief intake structuring
Claude Opus 4.7
Claude Sonnet 4.6
Highest accuracy on long ambiguous text
Vendor relationship intel
Claude Sonnet 4.6
Claude Haiku 4.5
Fast continuous refresh
Risk synthesis
Claude Sonnet 4.6
Claude Haiku 4.5
Multi-source aggregation
Anomaly detection
Claude Haiku 4.5
noneLightweight pattern matching
Contract sanity check
Claude Opus 4.7
Claude Sonnet 4.6
Legal-grade review
Visual mood-board match
Claude Sonnet 4.6 (vision)
noneImage embedding + similarity
Recap deck composition
Claude Sonnet 4.6
noneLong-form generation
Burn forecast
Claude Haiku 4.5
noneNumeric extrapolation
Pattern detection (cross-event)
Claude Sonnet 4.6
noneSoft clustering
Standup brief composition
Claude Sonnet 4.6
noneDaily generation
This week's model spend
Open AI cost dashboard

Total tokens used

12.4M

Total cost

$487

Avg latency

2.1s

P95 latency

4.8s

AI flags, doesn’t fix · every threshold change is logged and reversible · 24 active policies govern the system