Autonomous Multi-Agent SystemPaperclip + OpenClaw

Provider onboarding
at machine speed

40 AI agents orchestrated as a company — from intake form to filled licensing application across 10 US states, with human oversight at every step.

40
Agents Active
10
States Covered
$0.02
Avg Cost
~30s
Avg Time
0.9
Confidence Gate

Corporate Agent Structure

Structured as a company, not a flat swarm. Each agent has a role, scope, and budget.

Executive
2 agents
CEO
COO
Department
4 agents
VP-Licensing
VP-Compliance
VP-Comms
VP-Quality
State Directors
10 agents
CA
TX
FL
NY
MI
NV
IN
OH
GA
IL
Specialists
20 agents
DocExtractor
ComplianceChecker
FormFiller
CoachWriter
Validators
4 agents
ConfidenceGate
RegressionTester
CostMonitor
SafetyAuditor

Onboarding Pipeline

📋
Intake
Frontend
👔
CEO
Routes
📋
VP
Licensing
🏛️
Director
State
📄
DocExt
Extract
✅
Comply
Check
📝
Form
Fill
🔒
Gate
Score
💰
Cost
Budget

Reliability Patterns

🔒

Independent Confidence Gate

Separate adversarial judge (temp 0.1) scores all outputs. < 0.9 → human queue.

🔄

Multi-Model Cascade

Opus → Sonnet → MiniMax M2.7 with circuit breakers and exponential backoff.

📚

Knowledge Base RAG

State-specific regulations (TX Ch.746, CA Title 22, NY OCFS) injected into specialist context.

💰

Cost Circuit Breaker

CostMonitor tracks tokens per onboarding. $2 budget limit, auto-halt on overrun.

🛡️

Rule of Two

No single agent has PII access + external content + communication capability.

♻️

Retry + Degraded Fallback

2 attempts with backoff. On failure: degraded result → guaranteed human review.

Stack

Orchestration
Paperclip
Org chart, budgets, governance
Runtime
OpenClaw
Agent lifecycle, MCP, sub-agents
AI Models
4 models
Opus · Sonnet · MiniMax · Codex
Observability
HookWatch
OTel traces, span tree, cost