Why Verun

One wrong autonomous action is all it takes.

Agents now issue refunds, move money, send emails, and change data — and a single wrong action costs real money, customers, and trust. Enterprises have visibility, policies, and content guardrails, but at the moment an agent is about to act, nothing independent asks: should this happen — is it normal for this agent, and is it still on mission?

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AUTHORITYGAPshould it act?OrchestrationLangGraph, CrewAIObservabilityDatadog, LangfuseSecurityAuth, RBACGuardrailsContent filters

The tools exist. The gap remains.

Orchestration routes tasks. Observability explains what happened after the fact. Auth and RBAC decide who can connect. Content guardrails screen prompts and outputs. Each does its job.

None of them sit in the path of a consequential action and ask whether it should proceed. They govern access and content — not behavior.

Verun occupies that gap. It evaluates each action against policy, the agent's own behavioral baseline, and its declared mission — in real time, before execution — and returns ALLOW, HOLD, BLOCK, or ESCALATE with a signed receipt.

Three questions, asked on every action.

Most tools answer only the first. Verun's moat is the next two.

Can it?01

Policy

Allowed tools, thresholds, environment restrictions, mandatory approvals. Default-deny. Deterministic — no LLM in the path.

Does it usually?02

Behavior

A per-agent baseline flags velocity bursts, first-seen targets, cross-domain behavior, and unusual sequences. UEBA for agents.

Should it?03

Mission

A deterministic off-topic tripwire that holds actions drifting from the agent's declared purpose for human review. Robust intent verification is on our roadmap.

Can we prove it?04

Receipts

Every decision is a signed, tamper-evident, replayable record — which layer decided and why. Exportable as Governance Evidence Packs.

The Stakes

The numbers define the urgency.

62%

of organizations are already experimenting with AI agents

Source: McKinsey 2025
40%

of agentic AI projects may fail by 2027 due to cost, governance, and operational control gaps

Source: Gartner / Reuters 2025
82%

of organizations deploy AI agents, but only 44% have formal governance structures in place

Source: SailPoint / Zartis 2025
<10%

of enterprise applications are considered fully observable in complex AI-driven workflows

Source: IBM 2026
Adoption is a differentiator too

Prove it on your real traffic before you enforce anything.

Design-time and post-hoc tools can't offer this: a zero-risk trial on live agent behavior, and a policy mined from what it actually saw.

Shadow mode

Start in shadow mode. Zero risk.

Turn Verun on in observe mode and it changes nothing. It records what it would have allowed, held, or blocked on your real agent traffic — so you see the evidence before you enforce a thing.

Moat
Mined policy

Then it drafts your first policy for you.

From what it observed, Verun mines a policy — deterministic, explainable, every rule backed by the traffic that justifies it. Nobody writes rules from a blank page; you review and approve.

Additive

Additive, not a rip-and-replace.

One checkpoint call over the agents you already run. Verun complements your stack — it doesn't replace your orchestration, your models, or your tools.

Why now / Why not the cloud giants

The neutral behavioral layer.

AWS, Microsoft, Kong and Palo Alto will own the gateway and policy plumbing. None is structurally positioned to own per-agent behavioral memory across OpenAI, Anthropic, local models, and many frameworks at once. That's Verun's lane.

Cloud-native guardrails & gateways

  • Single-stack — strongest inside their own cloud and models
  • Govern content and access — screen text, authenticate callers
  • Ship primitives — a policy language, a gateway, a filter
  • No per-agent behavioral baseline that compounds over time
  • Conflict of interest in observing rival providers neutrally

Verun

  • Cross-stack — any framework, any model provider, any deployment
  • Governs behavior — what the agent does, against its own baseline
  • A behavioral product, not a primitive — value compounds on top
  • Per-agent baselines that improve with cross-customer volume
  • Neutral by design — no incentive to favor one provider

Only a neutral layer can hold behavioral memory across every provider an enterprise uses — and those baselines compound with every allow, hold, block, and human ruling. Verun is the CrowdStrike + UEBA for AI agents.

Ready to close the gap?

See how Verun authorizes agent actions in real time — or start a pilot.