Define what your AI agents are allowed to do. Watch what they actually do. Act the moment those two things diverge.
LangChain · CrewAI · Copilot Studio · Agentforce · Any custom agent
Attempted €43,200 SAP payment → awaiting Finance Director approval (4h SLA)
[Would have sent 341 CRM records to external_email — blocked in Enforce Mode]
The risks aren't hypothetical. They're happening inside companies just like yours, right now.
"Your developers deployed 6 agents last quarter without going through IT. Three have read access to the CRM. Two can send external emails. You found out when a customer called asking why they'd received a message from your company."
"Finance Bot approved a €43,200 invoice at 2:14am on a Thursday. The payment cleared before anyone saw the Slack notification. The €10K limit existed in a system prompt — not in any enforced policy."
"Sales Bot reads the full CRM (approved). Sales Bot sends external emails (approved). Nobody checked: together those two permissions create a path where the agent can read 3,000 customer records and email them externally. No single policy caught it."
"Your AI agent made 847 decisions last month. The auditor asks: 'Show me the Behavior Contract this agent was operating under, and the authorization basis for each decision.' You have logs. You don't have policies."
"Which agents have access to financial systems right now — and what can each one spend without approval?"
"Show me the formal governance policy for Agent X — not the system prompt, the enforced boundary."
"What input triggered that 2am action — and who was supposed to have approved it?"
"If Agent Y is compromised — who holds the kill switch and how fast can we stop it?"
"Show me an audit trail for all external data transfers by AI agents in the last 90 days, mapped to their authorization basis."
Complexity answers all five. In one platform.
See how it works →Every competitor owns exactly one layer of the governance problem. None of them own the whole stack.
Every competitor owns one layer. JetStream is excellent at defining what agents should do — but has zero approval workflow to stop them doing what they shouldn't. Noma finds threats brilliantly — but once agents are running, there's no identity layer, no authorization flow. Agendex has the most technically correct enforcement architecture in the market. It has no UI. A CISO cannot interact with it.
Every competitor was built by engineers, for engineers. Python DSLs. YAML policies. CLI tools. The CISO who needs governance most does not write Python. The Finance Director whose agents approve invoices doesn't want to review YAML. The buyer who holds the budget is almost never the one who can write code. Complexity is the only platform where every governance function has a visual, non-technical interface.
Every observability tool presents information. None of them let you act from the same surface. Without inline actions: see incident → navigate to queue → find item → review context → act. That's 4–7 minutes. In enterprise payment systems, the SLA has already elapsed. With Complexity's inline actions: see incident → approve. 8 seconds. The feed is not just a monitoring surface — it's the control plane.
"How do we prove this is working?" Every competitor fails this question. JetStream shows logs — proves you're logging, not governing. Noma shows red team findings — proves vulnerabilities, not remediation. Nobody has a single number that tells the board how well the organization's AI agents are governed. The Governance Score is that number.
Shadow Mode means nothing is blocked until you say so. Every step is reversible. Start today.
Connect any agent from any platform. Every new agent starts in Shadow Mode — Complexity observes all actions and annotates what governance would do. Nothing is blocked. Nothing changes in your operations.
Which tools can it use? What data can it access? What outputs can it produce, and up to what financial threshold? Visual form — no code required. A CISO completes it. No engineer in the room.
Observability feed shows every action. Approve, deny, create policy, kill-switch — all inline. Smart Queue prioritizes the €43,200 invoice over the €150 email. Pre-authorize routine actions.
Governance Score 0–100. Component breakdown. EU AI Act Article 14 evidence package. "Score went from 31 to 82 in 6 weeks." That sentence ends the board conversation.
Four roles. Four specific fears. One platform that answers all of them.
"47 agents across 6 platforms. 3 are unregistered. 2 have MCP connections not on any approved list. I don't know what the combination of their tool permissions creates in terms of attack surface — and the board is asking."
Every agent has an identity and a Behavior Contract. Toxic Flow Analysis surfaces dangerous tool combinations no individual policy catches. Shadow Mode: full visibility before a single rule is enforced.
"Finance Bot approved €43,200 at 2am. The limit existed in a system prompt — not in any enforced control. I can't show auditors what the agent was 'permitted to do.' I have logs, not policies."
Behavior Contracts define financial thresholds as runtime-enforced policies. Smart Queue surfaces the €43,200 first. Pre-authorization handles routine approvals automatically.
"EU AI Act Article 14 requires demonstrable human oversight. We're being asked to document what our agents are 'allowed to do' versus 'actually did.' We have telemetry. We have no governance policies."
Behavior Contracts are compliance artifacts. Data Flow Policy Builder creates contextual rules without code. One-click compliance report — EU AI Act, ISO 42001, SOC 2.
"When an agent goes wrong, my options are: code rollback, manual API key revocation, or killing the whole service. There's no way to stop one agent without collateral damage."
Per-agent kill switch in one click. No code. Shadow Mode rollback without disabling the agent. Anomaly alerts before the incident reaches your ticket queue.
Most are good at one thing. None are good at everything. Here's exactly what they have and what they're missing.
"JetStream has blueprints but no toxic flows and no pre-action visual block. Noma has red teaming but no identity management and no approval workflows. Nobody else has all five: shadow-mode safe onboarding, dollar-quantified risk, visual toxic flow detection, pre-action authorization, and a governance score your board can track."
Start with Shadow Mode — see exactly what governance would do before you enforce a single rule.
Governance dry-run on your first 3 agents.
Full governance for production AI deployments.
Unlimited agents, compliance requirements, custom deployment.
All plans include: Agent identity registry · Behavior Contracts · Shadow Mode · Observability feed
Shadow Mode means zero risk to your existing operations. Start observing today. Enforce when you're confident.
First unauthorized action flagged: within 48 hours for 90% of customers.