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SOVIGL returns approved, pending, or blocked for any action.

Project description

SOVIGL

Policy enforcement and audit layer for AI agents.

Every action your AI takes - governed before it executes. pip install sovigl

What it does

SOVIGL sits between your AI agent and the action it wants to take. Before anything executes - payment, approval, data operation

  • SOVIGL evaluates it against your policy and returns one of three outcomes:

  • APPROVED - executes immediately

  • PENDING - held for human approval

  • BLOCKED - stopped permanently

Every decision is permanently recorded with a unique ID, plain English explanation, risk score, and the exact policy version that triggered it.

Quick start

import sovigl

sovigl.configure(api_key="your-key", org_id="your-org")

decision = sovigl.evaluate(
    action="payment.create",
    context={
        "amount": 5000,
        "role": "employee",
        "user_id": "user_123",
        "agent_id": "invoice_bot"
    }
)

print(decision.status)               # approved
print(decision.decision_id)          # permanent audit ID
print(decision.reason)               # why it was approved
print(decision.risk_assessment)      # risk score 0.0-1.0
print(decision.explanation_registry) # full explainability
print(decision.policy_version)       # which policy version
print(decision.approved)             # True

Demo - no signup needed

Try it instantly with the demo org:

import sovigl

# No configuration needed for demo
decision = sovigl.evaluate(
    action="payment.create",
    context={"amount": 5000}
)

print(decision.status)      # approved
print(decision.decision_id) # permanent ID
print(decision.reason)      # plain English reason

Live dashboard: https://web-production-e334b.up.railway.app/dashboard

Full response object

evaluate() returns a Decision object:

Field Type Description
status string approved / pending / blocked
decision_id string permanent immutable audit ID
reason string why this decision was made
explanation_registry dict full explainability record
risk_assessment dict risk score 0.0-1.0 + factors
policy_version int which policy version was active
approval_id string human approval reference
summary string plain English summary
approved bool True if status == approved
pending bool True if status == pending
blocked bool True if status == blocked
raw dict complete backend response

What makes it different

  • Pre-execution gate - nothing executes without a decision. Not post-execution logging.

  • Policy versioning - auditors know exactly which rule was active at decision time.

  • Business policy engine - amount thresholds, role-based routing, mandate enforcement, fraud detection built in.

  • Compliance evidence - every decision automatically satisfies EU AI Act Art.12/13/14, MAS FEAT, NIST AI RMF, RBI FREE-AI.

  • Fully hosted - no self-hosting needed. Works in an afternoon.

Context fields

Field Type Description
amount number Transaction amount
role string employee / manager / admin
user_id string Who is performing the action
agent_id string AI agent identifier
description string Optional note

Action types

Any string in dot notation:

  • payment.create
  • expense.submit
  • transfer.initiate
  • loan.approve
  • vendor.onboard
  • data.export

Pending workflow

decision = sovigl.evaluate(
    action="payment.create",
    context={"amount": 25000, "role": "employee"}
)

if decision.pending:
    # Route to human approver
    print(f"Approval required: {decision.approval_id}")
    print(f"Reason: {decision.reason}")

Node.js

const sovigl = require("./node/index.js");

const decision = await sovigl.evaluate({
    action: "payment.create",
    context: { amount: 5000, role: "employee" }
});

console.log(decision.status);      // approved
console.log(decision.decision_id); // permanent audit ID
console.log(decision.reason);      // why

Production access

Email sovigl100@gmail.com to get your org_id and api_key.

Free during beta. No credit card. No commitment.

Links

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