Zenity finds and secures your agents. Prefactor knows if they are doing their jobs.
One finds shadow agents and flags injection or leakage, the other evaluates each outcome for quality, cost, and approved scope, so they sit at different layers.[1]
What is the difference between Zenity and Prefactor?
Zenity is the security layer for deployed agents: shadow discovery, threat detection, and posture management. Prefactor evaluates each run's outcome: quality per agent and version, drift after a change, and cost. A secure agent can still return the wrong answer, so many teams run both.
Zenity or Prefactor, in one table
| Decision factor | Zenity | Prefactor |
|---|---|---|
| Where it fits | Securing the agent against attacks | Knowing the agent did its job in production |
| Primary question | Is this agent being attacked or misused? | Did this agent produce the right outcome, at what cost? |
| Threat model | Adversarial: someone misusing the agent | Operational: drift and scope creep, no attacker required |
| What you get | Threat detection and response across agents | A quality score per run, drift detection, and cost per agent |
| How it attaches | Security monitoring across your agent estate | Native SDK, core SDK, or OpenTelemetry ingest, no rebuild, no gateway in the request path |
| Use them together? | Watch for attacks with Zenity | Evaluate the work with Prefactor |
What each one is for
- Shadow agent discovery: finds agents across SaaS, cloud, and endpoint environments, including ones nobody registered.
- Runtime threat detection: prompt injection, data leakage, and over-permissioned behaviour, flagged as it happens.
- Security posture management: aligned to OWASP LLM Top 10, MITRE ATLAS, and NIST AI RMF.
- Incident correlation: agent-level correlation and intent-focused threat analysis for a security team to act on.
- Recognition: Gartner Cool Vendor 2025 in Agentic AI TRiSM, with Fortune 500 customers.
Best for security teams that need to detect and respond to threats across their deployed agents.
- Evaluates every run for outcome quality, cost, and whether the agent stayed in its approved scope.
- A quality score per agent tracked across versions, so a regression shows up as a trend rather than a surprise.
- Drift detection when behaviour shifts after a model update or a prompt edit, before a user hits it.
- Holds or escalates a risky action for review before it reaches a user, not after, once a score or scope check crosses a threshold.
- One record across frameworks: agents evaluated from the same place, with an audit trail for each decision.
Best for teams running agents in production who need to know each one is doing its job, and prove it.
Side by side, security versus evaluation
| Capability | Zenity | Prefactor |
|---|---|---|
| Securing the agent | ||
| Shadow agent discovery | ✓ | — |
| Runtime threat detection (prompt injection, data leakage) | ✓ | — |
| Security posture management (OWASP, MITRE ATLAS) | ✓ | — |
| Evaluating agents in production | ||
| Quality score per run | — | ✓ |
| Cost attributed per agent and version | — | ✓ |
| Drift detection against a baseline | — | ✓ |
| Hold or escalate a risky action before a user is affected | On threat signals | On quality and scope signals |
| Across your stack | ||
| Evaluates agents built on any framework | — | ✓ |
| One queryable record per agent | — | ✓ |
| Audit trail for a decision | For security incidents | ✓ |
Where security stops: whether the agent did its job
We sell the layer this section describes. Read it with that in mind.
Zenity answers whether an agent is under attack or acting outside its permissions, and it does that work well. It does not say whether the agent did its job, at acceptable quality and cost, with evidence you can show.
Each run is measured against the agent's job, and the quality score is tracked per agent across versions.
When behaviour shifts after a model update or a prompt edit, Prefactor flags it.
When a score or a scope check crosses a threshold, Prefactor can hold or escalate the action before a user is affected.
Every decision keeps a record you can give to a customer or an auditor. Prefactor reads the traces you already emit, through a native SDK or any OpenTelemetry source, so it runs alongside Zenity rather than replacing it.
Which one fits
Reach for Zenity when
- Your priority is detecting attacks and misuse across deployed agents.
- A security team owns the agent estate and needs threat response.
- Shadow agents and over-permissioned behaviour are the immediate risk.
Reach for Prefactor when
- Agents are doing real work for real users and quality matters per run.
- You need a quality score per agent and version, not just a threat alert.
- A regression after a prompt or model change has to surface before a user hits it.
- Someone asks you to prove an agent did its job.
How we reviewed this comparison
Reviewed against public product and documentation pages on March 19, 2026. If a vendor has changed a feature, product name, or positioning since then, send a correction and we will update it. Numbered source links in the page body point to the ordered sources below.
Sources reviewed
Prefactor contextMethodology
- Reviewed public product, documentation, and launch material visible at the time of writing.
- Mapped each page to the primary buyer, control layer, and runtime capabilities each vendor describes publicly.
- Prefer direct product and documentation pages over analyst summaries or reseller material.
Does Prefactor replace Zenity?
Can Prefactor detect prompt injection?
What does Prefactor do that Zenity does not?
Does Prefactor work with agents Zenity already monitors?
Which team buys Prefactor?
Related
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