Priya · Admin Dev · Submitter Arun · Reviewer Sandra · CRO
AI Control Plane / Integrate
SDK & Integration Integrate Aegis with your existing AI infrastructure. Connect model registries, observability tools, and data platforms to automate governance workflows.
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governance checks
QUICKSTART
Python Node.js REST
# Install
pip install aegis-ai
# Initialize
from aegis import AegisClient
client = AegisClient(api_key= "aeg_prod_xxxxxxxxxxxx" )
# Log a governance decision
response = client.governance.check(
agent_id= "fraud-detection-v2" ,
action= "transaction_review" ,
context={
"confidence_score" : 0.94,
"risk_score" : 0.12,
"transaction_amount" : 4200.00
}
)
print (response.decision) # ALLOW
print (response.pattern_type) # BASELINE
print (response.latency_ms) # 38 RESPONSE FORMAT
Every governance check returns a structured JSON response. Decisions are either ALLOW or DENY.
✓ ALLOW
{
"decision" : "ALLOW" ,
"policy_id" : "pol_sr117_001" ,
"reason" : "Within approved parameters" ,
"latency_ms" : 23
} ✗ DENY
{
"decision" : "DENY" ,
"policy_id" : "pol_sr117_002" ,
"reason" : "Risk score exceeds threshold (0.72 > 0.70)" ,
"latency_ms" : 18,
"pattern_triggered" : false
} API KEYS + Generate Key
Name Key Status Last Used Created No API keys yet. Click "+ Generate Key" to create one.
CONNECTED SYSTEMS
No systems connected yet.
Make your first governance check to see it appear here.
Event Types
policy.violation model.approval_required audit.generated
CONNECT YOUR TOOLS
Stream governance events to Datadog as custom metrics and logs. Monitor policy violations alongside your existing observability stack.
Register models trained in Databricks directly into the Aegis registry via API. Trigger governance checks on every model version.
Connect Azure ML model deployments to Aegis for automatic SR 11-7 audit trail generation.
Register AWS SageMaker endpoints in Aegis registry and apply governance policies at deployment time.