Head-to-head · updated 13 September 2026
DataShield vs Noma Security: breadth of coverage, or proof of what happened?
Noma Security is the most serious competitor on this list, and pretending otherwise would waste your afternoon. They've raised $132M, they ship discovery, posture management, red teaming and runtime protection in one console, they added agent-level access control for MCP servers in June 2026, and in July they became a named integration partner for Anthropic's Claude Compliance API. If your question is "what AI is running across my whole estate and is any of it dangerous", they answer it and we don't.
Our question is narrower and starts later. Once an agent is already touching regulated data, can you prove which calls were allowed, get a masked value back when Legal needs a lawful re-identification, and pull an agent's authority mid-job? Datasets are tokenized at ingest; agents query tokenized data over MCP; detokenization is a privileged, audited operation. Every governed call is sealed into a hash chain your auditor can check without our cooperation. Here's where the two actually differ, with sources.
The short version
Pick DataShield when
- An examiner will one day ask you to prove an agent's access log wasn't edited, and "it's searchable" isn't an answer. Ours is a hash chain with signed, chained checkpoints. Run the verifier.
- Masking one-way would break you. Your fraud team joins across datasets, and Legal occasionally has to re-identify a subject lawfully. Our tokens are deterministic, join-preserving and vault-reversible.
- You need an agent's authority pulled mid-session, with the very next governed tool call failing closed rather than waiting for a policy sync. How Auth does it.
- You'd rather see a price than start a quarter-long procurement cycle.
Pick Noma when
- You don't yet know what AI is running. Their continuous discovery and shadow-AI inventory is real work we simply don't do, and you can't govern agents you can't see.
- You want AI-SPM, supply-chain posture and red teaming in the same console as runtime protection. All three are out of our scope.
- Your estate is Copilot Studio, Agentforce, ServiceNow, Bedrock, Databricks. They cover those platforms; we cover MCP-native agents on regulated data.
- You need inline masking of PII before a model sees it. They sit in traffic and do that. We deliberately don't sit inline, and we won't claim we do.
Bottom line: Noma secures the AI estate. DataShield produces the evidence and the reversibility that a regulator, not a CISO dashboard, will ask for. If your exposure is a wide fleet of unknown AI, start with them. If it's a small number of agents touching data you're legally accountable for, start here.
Feature by feature
Competitor cells describe what Noma's public site, launch posts and newsroom say as of the date above. If we've mischaracterised something, email support@myorg.ai and we'll correct it, credited.
| What matters | DataShield | Noma Security | Edge |
|---|---|---|---|
| Audit evidence | SHA-256 hash chain with Ed25519-signed checkpoints that are themselves chained. Verification names the failure: tampering, insertion, deletion, or truncation. Public verifier. | A "complete audit trail" that is logged and searchable. We found no published cryptographic tamper-evidence mechanism. | ◆ |
| Agent authorization | Every governed tool call passes a scope ceiling, an authority tier, and a revocation re-check before dispatch. Revocation lands on the next call. | Agentic Access Control: attributable agent identity per MCP server, with tool-level Approved, Requires-Review and Blocked states. Those are policy assignments; per-call revocation behaviour isn't described. | ◆ |
| Break-glass | Scoped, time-boxed emergency access for agents that auto-revokes and can't be quietly deleted from the log. | Nothing published. | ◆ |
| Data handling | Deterministic, join-preserving, vault-reversible tokens applied at ingest, plus k-anonymity generalization of quasi-identifiers. Detokenization is a privileged, logged operation. | Real-time masking of PII, credentials and API keys inline, before the model sees them. Masking is one-way, so joins and lawful re-identification don't survive it. | ◈ |
| Inline runtime protection | None, by design. Agents query already-tokenized datasets over MCP, so raw values never enter the queryable surface. | Yes. "Detect. Mask. Block." in the live path, including blocking poisoned MCP servers and malicious tools. | ◇ |
| 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 erasure. | Compliance tracking against GDPR and other frameworks. We found no erasure execution story. | ◆ |
| Discovery and posture | An MCP services registry for our own control plane. No cross-estate discovery, no AI-SPM, no supply-chain scanning. | Continuous AI discovery, shadow-AI inventory, posture management and supply-chain checks for poisoned models and data. | ◇ |
| Red teaming | Not offered. | Automated AI red teaming as part of the platform. | ◇ |
| MCP and agents | Native MCP endpoints on Auth, Ontology and Lighthouse. MCP tool tokens with scope ceilings, per-call metering attributed to the agent. | A dynamic agent-to-MCP-server registry with tool-level policy states. No per-call metering or chargeback attribution described. | ◈ |
| Deployment | Self-hosted, in your VPC, or BYOC. Your keys. | SaaS or on-prem and self-hosted, with the claim that no model, data or security events need leave the environment. AWS Marketplace listed. | ◈ |
| Ecosystem reach | Model-vendor neutral by design. Our MCP tool tokens and audit chain don't depend on any one provider's compliance API. | Integrates with Anthropic's Claude Compliance API, embedded as a native guardrail in TrueFoundry and Amazon Kiro, plus a Kong gateway partnership. | ◇ |
| 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 2023, $132M raised, self-reported customers including UiPath, Best Buy and Nielsen. Growth figures are vendor-reported. | ◇ |
| Pricing | Published model, scoped instant quote, no sales wall. | Quote-only, priced per agents, MCP servers and integrations. No figures published. | ◆ |
◆ DataShield leads◇ Noma Security leads◈ comparable
Noma claims are drawn from noma.security, their launch posts and newsroom, last checked 13 September 2026. We link them below rather than paraphrase from memory.
Three things you get here that you won't get from an AI security platform
Proof, not search
"Complete audit trail" and verifiable audit trail are different claims, and only one of them survives a hostile question. A searchable log in anyone's store is still a mutable one. Ours is a hash chain with signed checkpoints, and the verifier names what went wrong: tampering, insertion, deletion or truncation. EU AI Act Article 12 and HIPAA §164.312(b) reviewers are looking for that property specifically. Try breaking ours, no account needed.
Protection you can undo on purpose
Masking is destructive. When a DSAR lands, or a fraud analyst needs to join two datasets, or Legal has a lawful basis to re-identify, a masked value is simply gone. We tokenize at ingest with deterministic, join-preserving tokens and treat detokenization as a privileged, audited vault operation. How the data plane works.
The Friday-afternoon revocation
An analyst leaves at 4pm. Their agent is 20 minutes into a 40-minute job. A policy state that says Approved stays Approved until something syncs it. We re-check authority on every governed tool call, so the next one fails closed. Break-glass is the same mechanism in reverse: scoped, time-boxed, and impossible to quietly delete from the log. How Auth does it.
Where Noma is genuinely stronger
Almost everywhere that isn't evidence or reversibility. Noma has roughly a hundred times our resources, a platform that spans discovery, posture, supply chain, red teaming and runtime, and named customers on the record. Their Agentic Access Control launch in June 2026 means our "we live in the MCP call path" line is no longer a novelty. They deploy on-prem as well as SaaS, so the self-hosting argument we use against pure SaaS vendors simply doesn't apply here. They're inline, which we are not, and they cover Copilot Studio, Agentforce and ServiceNow, which we don't touch. If a board asks your CISO to name the safe choice for securing the AI estate, that's them, and I'd say the same in their seat.
Where I'd argue back: breadth stops where evidence begins. Their access control assigns a state to an agent and a tool; ours re-checks authority on the call itself, which is the difference between a policy and an enforcement point. Their protection is one-way, which is fine until a regulator asks you to produce the subject's data or erase it on demand. And nothing in their public material claims a log you can cryptographically verify. Ask both of us for that. It's a short conversation.
Questions worth asking both of us
Ask these on every call in this category. Ours included, and ours especially.
Can you cryptographically prove an audit log entry wasn't deleted?
DataShield: yes, and you don't have to take our word for the result. Each row commits to the row before it, checkpoints are Ed25519-signed and chained to one another, and the verifier reports the failure by name rather than returning a red cross. There's a chain at /verify you can attack. Noma: their runtime page describes a complete, searchable audit trail. We found no published tamper-evidence mechanism. Ask them to show one, and ask who at their company could edit the store.
What happens to a revoked agent mid-session?
We re-read authority at dispatch on every governed tool call, so the call after your revocation fails, not the call after the token expires. Noma's model is tool-level Approved, Requires-Review and Blocked states assigned to agents; how quickly a state change reaches an in-flight session isn't described publicly. The Asana integration incident ran 34 days past the point it should have been cut off. Ask both of us for the number.
How does GDPR erasure interact with the audit trail?
Crypto-shred: the subject's key material goes, their data becomes unreadable, and an ISO 27560 receipt records it. Actor identities in the chain are HMAC commitments, so nothing in the log has to be deleted for the erasure to be real. Noma tracks GDPR compliance as a posture item; we found no erasure execution or crypto-shred story. Ask whether erasing a subject breaks the log, and whether masked data can be produced for a DSAR at all.
Noma masks PII inline. Doesn't that beat tokenizing at ingest?
For prompts typed by a human into a chat window, yes, inline masking catches things we never see. We don't sit in the traffic path and won't claim we do. The trade is reversibility: their masking is one-way by construction, so joins break and lawful re-identification is impossible. We tokenize datasets at ingest, agents query tokenized data over MCP, and detokenization is a privileged, audited operation. Different layer, different failure mode. A few buyers should run both.
They integrate with Anthropic's Claude Compliance API. What's your equivalent?
We don't have one, and we're not planning one. Our MCP tool tokens, scope ceilings and audit chain are model-vendor neutral by design, so the same evidence plane covers Claude, an in-house model, and whatever you migrate to in 2028. Noma's integration is a genuine advantage if your deployment is Claude-centric today and you want a control plane that speaks that provider's compliance surface natively. Weigh it against lock-in on a three-year horizon.
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 and have been in production since April 2026. We also have no named customers to hand you, which against a $132M competitor is a disadvantage, not a quirk. Source escrow is in the design-partner terms so one small vendor isn't a single point of failure. Security page.
- Noma's hero: "Secure AI. Control Your Agents." Primary CTA is a demo request. — noma.security, 13 Sep 2026
- $100M Series B led by Evolution Equity Partners, $132M total raised. — SecurityWeek, Jul 2025
- Agentic Access Control gives per-agent identity to MCP servers with tool-level Approved, Requires-Review and Blocked states. — Noma launch post, Jun 2026
- Runtime protection is "Detect. Mask. Block." with a complete, searchable audit trail. — noma.security/platform/runtime-protection, 13 Sep 2026
- Visibility and access governance for AI agents and MCP servers, independently reported. — Help Net Security, 2 Jun 2026
- EDPB names pseudonymization as a GDPR risk mitigation for AI models, which one-way masking cannot satisfy for re-identification. — EDPB Opinion 28/2024
Other head-to-heads
DataShield vs Skyflow
A privacy vault with an inline gateway, versus agent authority and proof.
DirectDataShield vs Strac
Inline MCP interception versus identity, evidence, and break-glass.
ComplementDataShield vs Zenity
Agent discovery above, enforcement and evidence below. Most buyers run both.
AllEvery comparison
Eleven vendors, one honest scorecard each.
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