Head-to-head · updated 13 September 2026
DataShield vs Protegrity: which tokenization platform can prove what your AI agents did?
Protegrity has been tokenizing sensitive fields since 1996. Banks, insurers and retailers run their protectors next to Snowflake, Databricks, an old Db2 box, and a core system nobody wants to touch. Their vaultless tokens are generated from a key rather than looked up in a vault, and they keep the shape of the field, so legacy schemas don't break. If your job is protecting a big, old, sprawling data estate, they are a serious answer, and we say so twice more below.
We do a narrower job. Datasets are tokenized at ingest; agents query tokenized data over MCP; detokenization is a privileged, audited operation. On top of that, every governed tool call is checked against the agent's current authority, and each decision is sealed into a hash chain you can verify without trusting us. Here is where the two really differ, with sources, including the rows Protegrity wins.
The short version
Pick DataShield when
- Someone will one day ask you to prove an agent's access log wasn't edited. An examiner, an internal auditor, or Article 12 of the EU AI Act. Our chain answers with math, not a policy PDF. Run the verifier.
- You need to pull an agent's authority mid-session and have the very next tool call fail, instead of waiting for a token to time out.
- You want the vault, the policy engine and the evidence to run on your own infrastructure, on keys you hold, as one stack rather than a fleet of protectors.
- You'd like to see a price before you book a call. Ours is published.
Pick Protegrity when
- Your estate is wide and old. Mainframe, Db2, Oracle, Teradata, Snowflake, Databricks, a dozen SaaS apps. Thirty years of connectors is a real asset and we do not have it.
- You need tokens that keep the shape of the field so downstream schemas and validators keep working untouched. Ours don't do that, on purpose.
- PCI scope reduction is the funded project. They have retail and travel case studies for it; we have no PCI story at all.
- You want data discovery and classification across the whole estate first. We govern data you already know about, we don't go hunting for it.
Bottom line: Protegrity protects the data. DataShield governs what an agent is allowed to do with it, and keeps proof. If your board is asking about the agents rather than the estate, start here.
Feature by feature
Competitor cells describe what Protegrity's public site, capability pages and press releases say as of the date above. If we've mischaracterised something, email support@myorg.ai and we'll correct it, credited.
| What matters | DataShield | Protegrity | 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. | Policy-based audit and reporting, positioned as audit scope reduction. We found no published cryptographic tamper evidence. | ◆ |
| Agent authorization | Every governed tool call passes a scope ceiling, a declared authority tier and a revocation re-check before dispatch. Revocation lands mid-session. | "Verify agents" is the hero line, and Team Edition offers agentic policy creation. We found no described per-call token or authority mechanism. Worth asking them. | ◆ |
| Break-glass | Scoped, time-boxed emergency access for agents. It auto-revokes and can't be quietly removed from the log. | Not described in their public material. | ◆ |
| 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. | GDPR compliance is a stated outcome of field-level protection. The key-destruction mechanism and its effect on audit history aren't spelled out. | ◆ |
| Tokenization | Deterministic, join-preserving, vault-reversible tokens applied at ingest, plus quasi-identifier generalization (dates to year, decade or age band; ZIPs to 3 or 4 digits; partial phones, SSNs and emails) with a measured cardinality-reduction score per column. Detokenization is privileged and logged. | Vaultless tokens derived algorithmically from a secret key, no lookup vault in the path, field shape kept, referential integrity for joins. Plus FPE and dynamic masking. This is their home turf. | ◇ |
| Discovery and classification | We scan, profile and classify a live PostgreSQL source in place, with no rows leaving it. Columns get labelled against 129 field classes covering PII, PHI, financial data and secrets, and the catalog carries a business glossary, typed lineage and stewardship queues. That is PostgreSQL today, not your whole estate: SaaS apps, cloud stores and endpoints are not ours, and the other database providers are declared but not built yet. | ML-powered discovery across structured and unstructured data, including documents and logs. Shipped down to the free Developer Edition. | ◇ |
| Connector breadth | Modern stack. Postgres, DuckDB over Parquet, Snowflake keypair-JWT, eight credential strategies in the Connection Vault, and polling watch on S3, Azure Blob, GCS, SFTP and SMB. Nothing like their mainframe and legacy reach. | Protectors for data, application, cloud, SaaS and core systems, built up since 1996. Databricks Validated Partner since April 2026, plus Snowflake, Cloudera and Exasol. | ◇ |
| MCP and agents | Native MCP endpoints on Auth, Ontology and Lighthouse. MCP tool tokens with scope ceilings, and per-call metering attributed to the agent. | They've published thoughtful commentary on MCP governance, and Team Edition targets agentic workflows in tech preview. We found no MCP tool-token implementation. | ◆ |
| Inference guardrails | We do not proxy your LLM traffic. We do gate every value that leaves a governed dataset for a prompt: a PII or PHI column with no configured treatment is redacted, and a PHI dataset refuses any AI endpoint that is not marked BAA or ZDR approved. That is a gate on our own data path, not an inline product. | Semantic Guardrails inspect prompts and responses for injection and PII leakage, in every edition including the free one. | ◇ |
| Deployment | Self-hosted in your own cloud or data center, or on a dedicated single-tenant server we operate. Your keys. The whole stack, not an agent you install next to someone else's service. | SaaS, self-hosted, on-prem and hybrid, with listings on the AWS, Azure and Google Cloud marketplaces. | ◈ |
| Maturity signals | Auth, Guardian and Lighthouse are live in production (Guardian and Lighthouse since April 2026). SOC 2 not yet certified, and we say so. | Founded 1996. ISO 27001 certified, named Fortune 500 case studies, three hyperscaler marketplaces, a global partner network. | ◇ |
| Pricing | Published model, scoped instant quote, no sales wall. | Free Developer Edition on GitHub, then quote-only for Team and Enterprise. No dollar figures on any edition page. | ◆ |
◆ DataShield leads◇ Protegrity leads◈ comparable
Protegrity claims are drawn from protegrity.com capability pages and their own 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 a data protection platform
Proof that survives an audit
A log that can be edited without a trace has no evidentiary value. Ours is a hash chain with signed checkpoints, and the verifier tells you what went wrong, not just that something did. That's the property EU AI Act Article 12 and HIPAA §164.312(b) reviewers care about. Try it in your browser, no signup.
Authority that can change mid-flight
An analyst quits on a Tuesday. Their agent is 20 minutes into a 40-minute job. With DataShield the next governed tool call is re-checked against current authority and fails closed. Field-level protection alone won't stop that call, because the token is valid and the policy still says analyst. How Auth does it.
An erasure you can defend
GDPR says delete. Your auditor says keep the log. Crypto-shred settles it: the subject's key material is destroyed, the data goes unreadable, and the chain still verifies. See the diagram.
Where Protegrity is genuinely stronger
Let's be straight about the gap. Protegrity has been doing this since before most of our team could drive. Their vaultless tokens don't need a lookup on the hot path, they keep the shape of the field so downstream code doesn't care, and they hold referential integrity across joins. They classify sensitive data across structured and unstructured sources, they became a Databricks Validated Partner in April 2026, they ship on three cloud marketplaces, and in September 2025 they put a free Developer Edition on GitHub that you can run in Docker this afternoon. Thirty years of connector work is not something a smaller team talks its way around.
The push-back is about which boundary the control sits on. Protegrity is very good at the data boundary: what the field looks like, who may see it in the clear, what the model gets handed. The agent boundary is different. Gartner expects most unauthorized agent transactions through 2028 to be internal policy violations, not attacks. That means the agent had valid credentials and did something it shouldn't have. Their own September 2026 post is called "Insider Risk After Access Is Granted," which is the right question. Our answer is a mechanism: authority re-checked per governed tool call, break-glass with an expiry, and a signed chain that tells you afterwards what happened. Ask them for theirs.
Questions worth asking both of us
These are the questions we'd want answered if we were buying. Ask them on every vendor call, including ours.
Can you cryptographically prove an audit log entry wasn't deleted?
DataShield: yes. Each record commits to the one before it, checkpoints are signed and chained, and verification tells deletion apart from truncation and from tampering. Run it against a sample chain at /verify. Protegrity: their material describes policy-based auditing and audit scope reduction, and we found no published tamper-evidence mechanism. Ask them to show one.
What happens to a revoked agent mid-session?
DataShield re-checks authority on every governed tool call, so revocation bites on the next call. Protegrity's hero line says "verify agents," and their Team Edition covers agentic policy creation, but we couldn't find a described per-call authorization protocol in their public docs. Ask how long a compromised agent keeps working after you pull its access.
How does GDPR erasure interact with the audit trail?
DataShield crypto-shreds per-subject key material and issues an ISO 27560 consent receipt. Actor identities in the chain are HMAC-committed, so the evidence still verifies once the subject is gone. Protegrity lists GDPR among the regimes their protection supports, but the key-destruction step and its effect on audit history aren't described. Ask whether erasing a subject breaks the log.
Is DataShield a Protegrity alternative for enterprise tokenization?
Only for part of it. If you need field-level protection pushed into a mainframe, a dozen databases and a SaaS estate, they win and it isn't close. If your project is "our AI agents need to query customer data safely and we have to show our work," we're built for that. Our tokens are deterministic, join-preserving and vault-reversible. They are not shape-preserving, so a column that expected a 16-digit string will notice.
Protegrity has a free Developer Edition. What's your equivalent?
Free Demo Center access with a work email, where you can break a live audit chain and revoke an agent mid-session and watch the next call fail. Theirs is a different thing: a Docker install with discovery, protect APIs and Semantic Guardrails, released on GitHub in September 2025. If you want to write code against a protection API tonight, theirs is the faster path. We publish our pricing instead of gating the number.
Does DataShield have SOC 2?
Not yet, and we won't imply otherwise. Protegrity holds ISO 27001 and has been shipping since 1996, so on paper trail they are ahead. What we offer instead: Auth is live a public threat model and a verifier anyone can run. Guardian and Lighthouse have been in production since April 2026. Design-partner terms include source escrow, so a small vendor isn't a single point of failure. Details on the security page.
- Protegrity's current hero: "Protect data. Verify agents. Govern inference." Primary CTAs are "Book a demo" and "Start building for free". — protegrity.com, 13 Sep 2026
- Vaultless tokens are generated algorithmically from a secret key, with no central vault lookup, and keep referential integrity for analytics and joins. — protegrity.com capabilities, 13 Sep 2026
- Free Developer Edition released on GitHub with discovery, Find & Protect APIs and Semantic Guardrails 1.0, running locally in Docker. — Protegrity newsroom, 30 Sep 2025
- AI Team Edition announced as a tech preview for agentic workflows, covering agentic policy creation and semantic guardrails. — Protegrity newsroom, 17 Nov 2025
- Databricks Validated Partner status, covering tokenization, encryption and dynamic masking across Unity Catalog governed assets. — Protegrity newsroom, 10 Apr 2026
- ≥80% of unauthorized agent transactions through 2028 will be internal policy violations rather than attacks. — Gartner, 2026
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AllEvery comparison
One honest scorecard per vendor, including the rows we lose.
See both mechanisms run in your browser: break a live audit chain, revoke an agent mid-session, then decide whether you need us, Protegrity, or both. Demo Center access is free with a work email.
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