Head-to-head · updated 13 September 2026

DataShield vs Zenity: which layer does the audit obligation actually land in?

Zenity is the best-funded independent in agent security, and they earned it. If you have ten thousand citizen-developer agents in Copilot Studio and no idea who built them, Zenity will find them, score their posture, and flag the risky ones at runtime. Their current line is "Zenity secures long-horizon AI agents at the decision, the exact point where context and intent come together to create the highest risk." That's a sharper claim than most of this category manages.

DataShield sits one layer down, in the call path. Datasets are tokenized at ingest; agents query tokenized data over MCP; detokenization is a privileged, audited operation. Every governed tool call is checked against the agent's current authority before it dispatches, and the decision is sealed into a hash chain you can check without our help. This page is about which of those two jobs your compliance obligations actually require, and the answer is usually both, in a particular order.

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The short version

Pick DataShield when

You have to satisfy EU AI Act Article 12 and 26 or HIPAA §164.312(b). Those are logging and record-keeping duties, and they land on the enforcement layer, not the dashboard above it. Our chain is designed to map to them, and you can run the verifier yourself.
The agents that worry you touch PII or PHI. We classify it, generalize quasi-identifiers to k-anonymity, and tokenize at ingest. Zenity has no data plane.
You need an agent's authority pulled mid-session and the next tool call to fail, not an alert saying it already ran. How Auth does it.
Security says the evidence has to live in your own VPC with your keys. Zenity is SaaS only, so their logs live in their tenancy.

Pick Zenity when

Your estate is Microsoft Copilot and Copilot Studio, or Salesforce Agentforce. That's their home turf, including generally available inline prevention for Copilot Studio. We have nothing there.
You don't know what agents you have. Discovery and shadow-AI inventory across SaaS, homegrown, and device agents is a real product and we don't build one.
You want runtime anomaly detection with response playbooks. Their AIDR does intent-based detection. We're governance and evidence, not detection.
You're buying on maturity signals: Fortune 500 customers, $55M+ raised, a 2025 Gartner Cool Vendor listing and a 2026 "Company to Beat" mention. We're a small team with a v1.0 and two v0.2s.

Bottom line: Zenity tells you which agents are risky. We prove that what each governed call did was allowed, on data pseudonymized before the model saw it. Plenty of regulated buyers need both, and if you're sequencing, start with the layer the regulation names.

Feature by feature

Competitor cells describe what Zenity's public site and docs say as of the date above. If we've mischaracterised something, email support@myorg.ai and we'll correct it, credited.

What matters	DataShield	Zenity	Edge
Audit evidence	SHA-256 hash chain with Ed25519-signed checkpoints that are themselves chained. Verification names the failure: tampering, insertion, deletion, or truncation. Designed to map to EU AI Act Art. 12/26 and HIPAA §164.312(b). Public verifier.	Activity logs inside their SaaS tenancy. We found no published cryptographic tamper evidence.	◆
Agent authorization	In the dispatch path: scope ceiling, declared authority tier, mid-session revocation re-check, metering, then sealed audit.	Posture scoring plus detection and response. Third-party analyses note they don't secure MCP tool execution itself.	◆
Agent discovery	None cross-platform. We have an MCP services registry for our own plane and that's it.	Auto-discovery, shadow-AI inventory, ownership catalog across the estate. Genuinely strong.	◇
Runtime detection	Not our product. We decide and record; we don't score intent.	AIDR does intent-based anomaly detection with response playbooks.	◇
Break-glass	Scoped, time-boxed emergency access for agents that auto-revokes and can't be quietly deleted from the log.	Not described in their public material.	◆
Tokenization and data handling	Datasets are tokenized at ingest; agents query tokenized data over MCP; detokenization is a privileged, audited operation. Tokens are deterministic, join-preserving, vault-reversible. Plus classification, fingerprinting, and k-anonymity generalization.	No tokenization vault and no data-plane protection that we could find.	◆
GDPR erasure	Crypto-shred of per-subject key material plus ISO 27560 consent receipts. Actor identities are HMAC-committed, so the chain still verifies after the subject is gone.	Governance policies. Erasure of data an agent already processed isn't addressed in public docs.	◆
Platform coverage	MCP-native. Any MCP client or server tokenized by Auth. No Copilot, no low-code.	M365 Copilot, Copilot Studio with inline prevention GA, Agentforce, ChatGPT Enterprise, Bedrock, Vertex, Azure AI Foundry, plus surface-level coverage of Cursor and Claude Desktop.	◇
MCP and agents	Native MCP endpoints on Auth, Ontology, and Lighthouse. MCP tool tokens with scope ceilings, per-call metering attributed to the agent.	Agent-plane visibility rather than tool-level enforcement. Posture flags the risk; it doesn't block the call.	◆
Deployment	Self-hosted, in your VPC, or BYOC. Your keys.	SaaS only as of the date checked. Worth asking whether that's changed.	◆
Maturity signals	Auth v1.0 live. Guardian and Lighthouse v0.2, in production since April 2026. SOC 2 not yet certified, and we say so.	Founded 2021, $55M+ raised including Microsoft's M12, Fortune 500 customers, Gartner Cool Vendor 2025, "Company to Beat" 2026, Black Hat research through Zenity Labs.	◇
Pricing	Published model, scoped instant quote, no sales wall.	Unpublished and sales-led. No figures on their site.	◆

◆ DataShield leads◇ Zenity leads◈ comparable

Zenity claims are drawn from zenity.io and from our battlecard research, last checked 13 September 2026. Where we couldn't find something in their public docs we say so rather than asserting it doesn't exist.

Three things you get here that you won't get from a posture platform

Evidence, not a dashboard

When an examiner asks for the March logs, a risk score isn't an answer to the question they asked. Ours is a hash chain with signed checkpoints, and the verifier names the failure instead of just reporting one. That's what EU AI Act Article 12 and HIPAA §164.312(b) reviewers are looking for. Try the verifier, no account.

A decision in the call path

Posture tells you an agent is over-permissioned. It doesn't stop the call. Every governed tool call here passes a scope ceiling, an authority tier, and a revocation re-check before it dispatches. An analyst is offboarded mid-job and the next call fails closed. How Auth does it.

Protection on the data itself

Zenity secures the agent plane. Nobody in that layer tokenizes the PHI in the payload. We classify it, generalize quasi-identifiers, tokenize at ingest, and make detokenization a privileged, logged operation. The architecture.

Where Zenity is genuinely stronger

Almost everything about visibility. You can't govern what you can't see, and cross-platform agent discovery is a hard product that we have not built. If your Copilot Studio estate has grown to thousands of citizen-developer agents with no owner list, Zenity solves a problem we can't even describe for you. Their runtime detection is real, their Copilot integration goes as far as generally available inline prevention, and their research arm publishes work that lands at Black Hat. The Gartner recognition is earned, not bought attention.

And here's my objection. Their own analyst narrative cites a report titled "Emerging Tech: The Future of AI Security is in Securing Agent Actions, Not Prompts," which is the right instinct, and it points straight at a layer they don't occupy. Securing an action means being in the path when it happens and being able to prove afterward what you decided. Gartner also expects most unauthorized agent transactions through 2028 to be internal policy violations rather than attacks, and a policy violation by a correctly-behaving agent looks normal to an anomaly detector. So ask Zenity to block a specific MCP tool call in-band, or to reverse a pseudonym under policy, or to prove a log entry wasn't deleted. If the answers are no, that isn't a flaw in their product. It's the boundary of their layer, and it's where your Article 12 obligation lands.

Questions worth asking both of us

Put these to every vendor in this category, us included.

Can you cryptographically prove an audit log entry wasn't deleted?

DataShield: yes. Each entry commits to the one before it, Ed25519 checkpoints chain over the top, and the verifier tells a deleted row apart from a truncated tail and from an edited field. Go break the sample chain at /verify. Zenity: their activity logging lives in their SaaS, and we found no published tamper-evidence mechanism. Ask them to show one, and ask who at their end can edit a record.

What happens to a revoked agent mid-session?

Authority is checked at dispatch on every governed call, so a revocation stops the next one and the context drops with it. Zenity can detect and respond to anomalous behaviour, but we found no description of in-path authority tiers or mid-session revocation. Ask specifically: if I pull an entitlement while a 40-minute job is running, does the next tool call execute?

How does GDPR erasure interact with the audit trail?

Crypto-shred destroys the per-subject key material and produces an ISO 27560 receipt. The chain itself is untouched and still verifies, because the actors in it are HMAC commitments. Zenity documents governance policies; the handling of data an agent already processed isn't covered in their public material. Ask whether erasing a subject breaks anything downstream.

Should we run both?

Often, yes, and we'll say so on a call. A regulated enterprise with a large Copilot estate plus MCP-native agents on PHI legitimately needs discovery and posture from one vendor and enforcement plus evidence from another. Our view on sequencing: the regulation names logging and record-keeping, so fund the layer that produces the record first. Visibility is the upgrade, not the floor.

Does Zenity protect the data itself?

Not as far as we can tell. There's no tokenization vault and no data-plane protection anywhere in their public material, which makes sense given where they started, in low-code application security. So the EDPB's pseudonymization argument for AI models isn't a story they can tell. Ask them how PHI in a tool-call payload is protected before the model sees it.

Zenity has Microsoft's M12 on the cap table. Does that matter?

Maybe, depending on how you feel about the consolidation wave. We have no hyperscaler investor, which is a genuine difference but not a reason on its own to pick us. Judge it on whether you'd mind your agent governance vendor being acquired by the platform it's governing.

Does DataShield have SOC 2?

No. Auth is v1.0 with a published threat model and a verifier anyone can run. Guardian and Lighthouse are v0.2, in production since April 2026. Design-partner terms include source escrow, so a small vendor isn't a single point of failure. If SOC 2 is a hard gate this quarter, say so on the first call and we'll tell you whether to wait for us. Security page.

Zenity's current hero: "Secure AI Agents Everywhere," with the sub-head "Zenity secures long-horizon AI agents at the decision, the exact point where context and intent come together to create the highest risk." — zenity.io, 13 Sep 2026
Analyst proof devices on their site: "Company to Beat in AI Agent Governance," Gartner Cool Vendor in Agentic AI TRiSM (2025), and a cited report, "Emerging Tech: The Future of AI Security is in Securing Agent Actions, Not Prompts." — zenity.io, 13 Sep 2026
No published pricing. Sales-led, SaaS-only delivery, re-checked with no change since July 2026. — zenity.io, 13 Sep 2026
≥80% of unauthorized agent transactions through 2028 will be internal policy violations rather than attacks. — Gartner, 2026
EDPB names pseudonymization as a GDPR risk mitigation for AI models. — EDPB Opinion 28/2024
EU AI Act Article 12 requires automatic recording of events over the lifetime of a high-risk system; Article 26 puts log retention on the deployer. — EU AI Act, Regulation (EU) 2024/1689

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