§ COMPARISONS · LAST VERIFIED JUNE 2026
Execlave vs Zenity
Zenity is an enterprise AI agent security platform — AI Observability, AI Security Posture Management (AISPM), and AI Detection & Response (AIDR) — aimed at security teams securing agents across SaaS, Copilot, and homegrown estates. Execlave is developer-embedded runtime governance for the agents your team builds. This page lays out the deltas with a source link against every Zenity claim.
TL;DR
One paragraph if you are on the way to a meeting.
The honest one-liner
Zenity approaches agent security from the security-team, estate-wide angle: discover every agent across SaaS, Copilot, and homegrown platforms, harden their configuration and permissions, and detect and respond to threats at runtime — largely without per-app code changes. Execlave approaches it from the developer angle: embed policy enforcement directly in the agents you build, define block/approval gates in code, and produce signed compliance evidence. Both can detect prompt injection and block unsafe actions at runtime; the real difference is who operates it and how it is integrated. If your problem is “secure a sprawling agent estate I mostly did not build,” that is Zenity. If your problem is “bake enforcement and audit into the agents I am building,” that is Execlave.
The two products
Before the capability matrix, so we are talking about the same thing.
Zenity
An enterprise AI agent security platform (founded 2021) that unifies three capabilities: AI Observability (discover and inventory agents across platforms), AISPM (secure-by-design configuration and permission posture before deployment), and AIDR (runtime, intent-based detection and response that can block unsafe actions). Oriented to security teams and broad, largely agentless coverage across SaaS, Copilot, and homegrown agents. (zenity.io) (zenity.io/platform)
Execlave
A framework-agnostic runtime governance platform (managed SaaS or self-hosted) embedded at the code level via the SDK. Ships 19 built-in policy types, four enforcement modes, Slack-native approvals, three-tier prompt-injection scanning, hash-chained audit logs, signed compliance exports, and SIEM export over OTLP / Splunk HEC / Microsoft Sentinel.
Capability matrix
Every Zenity claim links to a Zenity-published source.
| Capability | Zenity | Execlave |
|---|---|---|
| Primary audience | Security teams securing AI agents across SaaS, cloud, Copilot, and homegrown estates (source) | Developers and platform teams embedding governance into the agents they build |
| Agent discovery / inventory | Core: AI Observability automatically discovers and inventories agents across platforms, with ownership and dependency mapping (source) | Not an estate-discovery product — governs the agents you instrument with the SDK |
| Posture management (AISPM) | Core: reviews agent configurations, permissions, memory, knowledge, instructions, actions, MCPs and tool integrations before deployment (source) | Not a configuration-posture product — enforces behavioural policy at runtime instead |
| Coverage model | Broad estate coverage including ChatGPT Enterprise, Microsoft Copilot Studio, and homegrown agents on Azure AI Foundry, AWS Bedrock, or Google Vertex AI — largely agentless (source) | Per-agent, code-level: any Python or TypeScript agent that calls the Execlave enforce API |
| Runtime detection & blocking | AI Detection & Response (AIDR) monitors agent intent and execution at runtime and can block unsafe actions before impact (source) | Four in-path enforcement modes (monitor / warn / require_approval / block) defined in code and evaluated by the SDK before the action proceeds |
| Prompt-injection detection | AIDR detects direct and indirect prompt injection via intent-based, cross-layer correlation (source) | Three-tier in-path scanner (heuristic → cache → local LLM) as the injection_scan policy type |
| Human-in-the-loop approvals | Security-team response playbooks and automated remediation at runtime (source) | Developer-defined Slack-native Approve / Deny on require_approval, with identity + timestamp + policy reference persisted |
| Compliance & standards | Posture policies aligned to OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF, and industry regulations (source) | Signed (RSA-SHA256-PSS) evidence packages mapped to EU AI Act, SOC 2, HIPAA, GDPR, ISO 27001, PCI DSS, NIST |
| Audit log integrity | Correlated findings and incidents (Zenity Issues) for investigation and response (source) | Append-only audit log with SHA-256 content chaining and DB-level UPDATE/DELETE denial |
| Integration approach | Connects to platforms to discover and govern agents largely without per-app code changes (source) | Code-level SDK (execlave-sdk, @execlave/sdk) plus SIEM export (OTLP / Splunk HEC / Microsoft Sentinel) |
When Zenity is likely the better fit
We would rather be honest than lose your trust.
Choose Zenity if…
- Your problem is estate-wide visibility — you need to discover and inventory agents, copilots, and homegrown apps you did not build and may not control.
- You are securing a large Microsoft Copilot / ChatGPT Enterprise or multi-platform footprint where embedding an SDK in every app is impractical.
- A central security team owns AI risk posture and wants detection & response and configuration hardening across the whole organisation.
When Execlave is likely the better fit
Cases where the architectural fit tips toward developer-embedded governance.
Choose Execlave if…
- You are building the agents and want governance embedded at the code level, with enforcement decisions defined in code and run in the request path.
- You need signed, offline-verifiable compliance reports (EU AI Act, SOC 2, HIPAA, GDPR, ISO 27001) an external auditor can verify with a published key.
- You want developer-defined approval gates wired to Slack, not only security-team response playbooks.
- You want a tamper-evident, hash-chained audit log plus SIEM export of every governance decision.
Running both in parallel
Estate-wide posture and response plus code-level enforcement.
Complementary deployment pattern
- Use Zenity for organisation-wide discovery, configuration posture, and runtime detection across Copilot and homegrown agents you do not directly build.
- Embed Execlave in the agents your team ships for in-path enforcement, developer-defined approvals, and a hash-chained audit trail.
- Export Execlave decisions to your SIEM so they sit alongside Zenity’s estate signals in one investigation surface, and generate signed compliance evidence from Execlave when auditors ask.
Sources
Everything cited above.
Zenity-published references
- zenity.io — home
- zenity.io/platform — platform overview
- Zenity — AI Observability
- Zenity — AI Security Posture Management (AISPM)
- Zenity — AI Detection & Response (AIDR)
Zenity’s product packaging evolves; verify current capability names against zenity.io. Spotted an outdated claim? Email support@execlave.com.