Head-to-head · updated 13 September 2026

DataShield vs Glean: the agent may read the record, but should the model see the SSN?

Glean is very good at the job it picked. Point it at your 250-plus SaaS apps and it builds an Enterprise Graph that knows who wrote what, who can see it, and which Jira ticket the Slack thread was really about. Permissions are inherited from the source system on every read and write. Their MCP Gateway precomputes the joins an off-the-shelf MCP tool would make the model do at runtime, which is a genuinely smart piece of engineering. They passed $300M ARR in May 2026. If your problem is that staff can't find anything, buy Glean and stop reading.

We do a different job. DataShield governs the structured and sensitive data agents act on: the customer table, the claims extract, the golden record. Datasets are tokenized at ingest; agents query tokenized data over MCP; detokenization is a privileged, audited operation. Every governed tool call is re-checked against the agent's current authority before it runs, and every decision is sealed into a hash chain you can verify without trusting us. Most buyers who talk to both of us end up running both. Here is the honest split, including the rows Glean wins outright.

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The short version

Pick DataShield when

The sensitive value must be a token before the model sees it, not a document the model was merely allowed to open. Permission filtering says yes or no to a whole file. We change what the field says.
Someone will ask you to prove an agent's access log was not edited. An examiner, an auditor, or Article 12 of the EU AI Act. Our chain answers with math. Run the verifier.
You need to pull an agent's authority mid-session and have the very next tool call fail. Not the next token refresh. The next call. How Auth does it.
The index, the keys, the policy engine and the evidence all have to sit on your own hardware. We ship Docker images and embed locally, so no text and no embeddings leave your network.

Pick Glean when

The actual problem is that nobody can find anything. 250-plus connectors and a precomputed Enterprise Graph are years of work, and we do not index Slack, Confluence or Google Drive at all.
You want permission-aware retrieval over unstructured documents. Glean inherits source-system permissions on every read and write, and they have been doing it since 2019.
Your security review wants certificates today. They hold SOC 2 Type II, ISO 27001, ISO 42001, HIPAA and TX-RAMP Level 2. We hold none of those yet.
You want a no-code agent builder, an agent library, trace views and an AI gateway from one vendor. Their Agent Development Lifecycle is a real operating model, not a slide.

Bottom line: Glean decides whether an agent may open the document. We decide what the data says when it gets there, and keep proof of the decision. Skyflow noticed the same gap and shipped a tokenization layer for Glean in August 2026, which tells you the market is real.

Feature by feature

Competitor cells describe what Glean's public site, blog and press releases say as of the date above. If we have mischaracterised something, email support@myorg.ai and we will correct it, credited.

What matters	DataShield	Glean	Edge
Enterprise search over SaaS apps	Not our product. Ontology has a real catalog and RAG over datasets and documents you load into it, but we do not crawl your Slack, your Drive or your Jira.	The core of the business. More than 250 connectors, an Enterprise Graph and a Personal Graph, plus a precomputed index that answers cross-app questions in one hop.	◇
Sensitive data before the model	Deterministic, join-preserving, vault-reversible tokens applied at ingest. Then a fail-closed prompt-egress gate: any PII or PHI column with no configured treatment is redacted before prompt assembly, and a PHI dataset refuses an AI endpoint not marked BAA or ZDR. 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.	Glean Protect adds sensitive-content policies, restricted-topics policies and oversharing detection. Their own framing is that sensitive content is detected and blocked, and documents can be hidden from results. We found no tokenization or generalization of field values in their public material.	◆
Audit evidence	SHA-256 hash chain with Ed25519-signed checkpoints that are themselves chained. The verdict is three-valued: clean, attested damage, or tampered. Re-tampering an attested chain un-attests it automatically. Try the verifier.	"Every control point is logged to an end-to-end audit trail as it happens, with events available to stream into SIEM." A good operational log. We found no cryptographic tamper evidence.	◆
Agent authorization	Every governed tool call passes session-authority revalidation, a metering guard, a consented-tool allowlist, a scope gate and an authority gate before dispatch. It fails closed.	Agent Access Policies (beta in May 2026) apply org-wide guardrails, and agent alignment models pre-scan write actions to flag misaligned attempts. That is a model checking a plan. Useful, and not the same as a deterministic gate.	◆
Agent identity	Agents are first-class subjects with SSO, MCP tool tokens carrying a scope ceiling, and RFC 8693 delegation with an enforced scope subset. Our subject model classifies human, service account and system. It is a classification, not a separate NHI product.	Genuinely strong, and they got there independently. Agent identity went to public beta in July 2026: an agent gets its own scoped service credentials, its own Slack bot and GitHub App, actions attributed to the agent with the triggering human recorded alongside, and admin rotate or revoke.	◈
Mid-session revocation	Session authority is revalidated on every governed tool call and downgrades to anonymous the moment it drifts. Revocation lands on the next call.	Admins can rotate or revoke an agent credential at any time, for one system or all. How fast that reaches a running agent is not described in their public docs. Worth asking.	◆
Break-glass	Scoped, time-boxed emergency access for agents, admin plus IP-allowlist plus step-up gated, fully audited, auto-revoking.	Not described in their public material.	◆
GDPR erasure	Crypto-shred of per-subject key material plus ISO 27560 consent receipts. Delete the subject key and every ciphertext for that subject goes dark at once. The audit chain still verifies afterwards.	GDPR compliance is listed on the security page. The erasure mechanism for indexed content and for the audit trail is not described. Ask what happens to an index built from a document you deleted.	◆
Retrieval and embeddings	pgvector with hybrid keyword and vector retrieval, and local `nomic-embed-text` embeddings, so no text and no vectors leave your network. Chunk views mask at read time and rebuild the keyword index from the masked text, so search cannot be used to probe for a redacted value. We publish no retrieval accuracy number, because we have no benchmark document to point at.	Better retrieval, and they should be. A precomputed index and knowledge graph across every connected app, tuned since 2019, plus 40-plus models to choose from. Their September 2026 benchmark claims 81% lower token cost and a 78% preference rate against one competing setup. That is their own test, but the architecture argument behind it is sound.	◇
Structured data and golden records	Ontology is a dataset platform: ingest, in-place scan and profiling of a live PostgreSQL source with no row egress, 129-class field classification with reproducible verdicts, typed lineage, stewardship queues, and MDM with Fellegi-Sunter probabilistic linkage, LSH blocking and five survivorship strategies. Golden records reach agents through views that mask unconditionally.	Interactive dashboards combine structured data with unstructured context, announced September 2026. The centre of gravity is documents and conversations. No entity resolution or master data layer is described.	◆
MCP and agents	More than 200 MCP tools across Ontology, Auth, Corpus and Lighthouse. Auth issues MCP tool tokens with scope ceilings and meters every call with agent attribution.	The MCP Gateway is the best part of their agent story. Permission-inherited connectors, OAuth through Glean's own authorization server with authentication delegated to your IdP, downstream tokens kept server-side, and access to more than 2,000 tools from one place.	◈
Deployment	Self-hosted in your own cloud or data center, or a dedicated single-tenant server we operate. Docker images for Auth, Ontology, Corpus and Lighthouse, with a signed deploy manifest Guardian verifies. Ed25519 audit-signing keys can live in your KMS or HSM. HMAC tokenization keys sit in your environment or derive from your machine key today, not in a KMS.	SaaS. The agent sandbox runs file system and code execution in the customer's own cloud, and at least one case study cites hosting Glean in the customer's tenant. A fully self-hosted edition is not offered publicly.	◆
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 2019. Past $300M ARR in May 2026, Fortune 500 customers nearly doubled year over year, 28 countries, SOC 2 Type II, ISO 27001, ISO 42001, HIPAA and TX-RAMP Level 2.	◇
Pricing	Published model, scoped instant quote, no sales wall.	Their pricing page is a demo request. No tiers and no per-seat figure are published.	◆

◆ DataShield leads◇ Glean leads◈ comparable

Glean claims are drawn from glean.com, the Glean blog and Glean press releases, last checked 13 September 2026. We link them below rather than work from memory.

Three things you get here that you won't get from an enterprise search platform

The model never sees the value

Permission-aware retrieval asks one question: may this person open this document? A fair question, and the wrong one when the document is a claims export with 40,000 member IDs in it. We tokenize at ingest, so the agent joins on TOK_9f2a... and gets a correct answer without ever holding the identifier. Detokenizing is a separate, privileged, tenant-scoped call, and the audit write has to succeed or the lookup is refused. How the data plane works.

Authority that can change mid-flight

An analyst leaves on a Friday. 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. Rotating a credential is the right move too, but it only helps on the next handshake. How Auth does it.

Proof that survives an audit

A log you can stream into a SIEM is a log an admin could have edited first. Ours is a hash chain with signed checkpoints, and the verifier names what broke: tampering, insertion, deletion or truncation. That is the property EU AI Act Article 12 and HIPAA §164.312(b) reviewers care about. Try it in your browser, no signup.

Where Glean is genuinely stronger

Almost everywhere our page doesn't go. Their connector estate is the deepest in the category and it took seven years to build. Their permission model, which mirrors source-system access on every read and write, is the thing every competitor quietly copies. The MCP Gateway argument is the sharpest technical writing any vendor in this market published in 2026: an off-the-shelf MCP setup makes the model reconcile Jira, Confluence and GitHub at runtime, while a precomputed index and knowledge graph do that join in advance. That is a real architectural insight, not positioning. Their agent identity beta, shipped in July 2026, reaches the same conclusion we did about agents borrowing human credentials, and their write-up of the problem is better than most of ours. They also hold the certificates we do not, and they have the logos.

Here is the push-back, and it is narrow on purpose. Every control they describe operates on documents and actions: hide the overshared file, block the restricted topic, flag the misaligned write, score the risky pattern. None of it changes what a permitted field contains. So the question a regulated buyer has to answer is what happens when the sensitive data sits inside a document staff are entitled to read. Glean's answer is a policy that hides the whole thing, which is why a professional-services CIO told Skyflow they would otherwise have had to "kill 60% of Glean's doc repos after legal found unsanitized client data." Skyflow launched a product for exactly that in August 2026. We think a token in the field beats a deleted repo, and we think the record of who detokenized what should be something an examiner can verify rather than something your vendor asserts.

Questions worth asking both of us

These are the questions we would want answered if we were the ones buying. Ask them on every call, ours included.

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 the verdict tells deletion apart from truncation and from tampering. Run it against a sample chain at /verify. Glean: their security page promises an end-to-end audit trail that streams to a SIEM. That is an operational log. We found no tamper-evidence mechanism in their public material. Ask them to show one.

What happens to a revoked agent mid-session?

DataShield re-checks authority on every governed tool call, so revocation lands on the next call. Glean's agent identity beta lets an admin rotate or revoke an agent's credentials for one system or all of them, which is the right primitive. What their docs do not say is how quickly a running agent notices. Ask how long a compromised agent keeps working after you pull its access, and ask for the number in seconds.

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. Glean lists GDPR on its security page but does not describe the mechanism. The interesting version of the question for an index is this: when a document is deleted, what happens to the chunks, the embeddings and the graph edges derived from it? Ask for the answer in writing.

Is DataShield a Glean alternative for enterprise search?

No. If your staff cannot find the onboarding doc, we are the wrong purchase and we will say so on the call. We have RAG over content you load into Ontology, with local embeddings and hybrid retrieval, but we do not crawl 250 SaaS apps and we are not trying to. Run Glean for finding things. Run us for the datasets agents read and write, where the obligation is tokenization, authorization and evidence.

Skyflow launched a product for Glean in August 2026. Why not just use that?

It is a reasonable choice and it validates the whole argument on this page: a tokenization vendor built a layer specifically to sanitize documents before Glean indexes them. Skyflow is a mature vault and does that job well. Where we differ is what comes after the token. We also carry the catalog, the classification, the per-call agent authorization, the mid-session revocation and the verifiable chain in the same stack, and we run entirely on your infrastructure. If you only need sanitized ingest, look at both of us. Our Skyflow comparison is honest about where they win.

Does DataShield have SOC 2?

Not yet, and we will not imply otherwise. Glean holds SOC 2 Type II, ISO 27001, ISO 42001, HIPAA and TX-RAMP Level 2, and on that row they beat us flat. What we offer instead is a published threat model, a verifier anyone can run, and design-partner terms that include source escrow so a small vendor is not a single point of failure. Auth is live, and Guardian and Lighthouse have been in production since April 2026. Details on the security page.

Glean's current self-description: "the trusted context and intelligence layer for enterprise AI," with Glean Tau, Glean Transform, an expanded AI Gateway and context-aware AI threat detection announced the same day. — glean.com press, 7 Sep 2026
Passed $300M ARR, Fortune 500 customers nearly doubled year over year, 85%+ of customers using Glean across five or more departments, presence in 28 countries. — glean.com press, 28 May 2026
MCP Gateway: permission-inherited connectors, OAuth through Glean's authorization server with authentication delegated to the customer's IdP, downstream tokens kept server-side, access to more than 2,000 tools. — Glean blog, 3 Jun 2026
Agent identity in public beta: agents act through their own scoped service credentials, with actions attributed to the agent and the triggering person recorded alongside. — Glean blog, 15 Jul 2026
Glean Protect: restricted-topics policies, pre-built sensitive-content policies, and agent alignment models that pre-scan write actions before they run. — Glean blog, 11 Mar 2026
"Enforce source-system permissions on every read and write"; "Every control point is logged to an end-to-end audit trail as it happens, with events available to stream into SIEM"; SOC 2 Type II, ISO 27001, ISO 42001, HIPAA, GDPR, TX-RAMP Level 2. — glean.com/security, 13 Sep 2026
Skyflow for Glean, launched 25 August 2026: "Sanitize the data. Control the results." Customer quote: "Without Skyflow we would have to kill 60% of Glean's doc repos after legal found unsanitized client data." — skyflow.com, 25 Aug 2026

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