Head-to-head · updated 13 September 2026

DataShield vs Stibo Systems: who should master your customer data for agents?

Stibo Systems has done master data since 1994. The parent firm dates to 1794. That is not a typo. Say your problem is 200,000 product SKUs, 1.7 million digital assets, supplier onboarding and channel syndication. Stibo belongs on your list. Gartner made them a Leader in April 2026. They booked a record year in June. Their STEP platform spans product, customer, supplier, location and sustainability data. They ship an MCP server so agents can read all of it. We won't pretend any of that away.

We compete on one slice of it: customer and party data. The part worth your attention is who builds the model. An agent interviews your business user. It writes a plan. It walks a decision gate with you, one choice at a time. Then it writes the entity types and trees. Plus draft match setups, reference links, and check rules. All in one save. Nothing masters anything until a frozen test run goes green. Under that sits matching you can open up: Fellegi-Sunter linking, named comparators, trained weights. Plus five survivorship rules. A golden record then has to earn the right to be read by an agent. Data gets tokenized at intake. Agents query tokenized data over MCP. Detokenizing is a special, logged step. Here is the honest split, rows Stibo wins included.

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The short version

Pick DataShield when

You want the model built with you, not sold to you. An agent runs the interview. You work a decision gate where each step shows what, why, impact and alternatives. The platform writes the draft model in one save.
The domain you actually need mastered is people and organisations, not SKUs. Customers, patients, members, counterparties, claimants.
Someone will ask you to prove an agent's access log was not edited. They'll also ask you to pull that agent's access mid-session. An auditor, an examiner, or Article 12 of the EU AI Act. Our chain answers with math, not a policy PDF. Run the verifier.
You want a golden record to earn agent access. Six quality checks, with published weights and a consent check that fails closed. The match logic, the vault and the keys all sit on your own setup, at a price you can see.

Pick Stibo Systems when

Product data is the job. PIM, digital assets, supplier onboarding, channel syndication, GDSN. We do none of it. We're not going to start.
You need many domains at once under one roof: product, customer, supplier, location, sustainability. Their six data clouds are a real portfolio, not a slide.
You are a big company with an SI already booked. Gartner MQ Leader, Forrester Wave Leader, 18 offices, and a foundation owner with no exit to chase. That's a safe board-level answer.
Your front office lives in Salesforce. You want mastered customer records pushed back into it, with duplicate prevention at the point of entry.

Bottom line: Stibo is the safe buy for product data at large scale. For party data that agents will read, two questions now matter most. Who built this model with you? Can you prove what the agent was allowed to do with it?

Feature by feature

Competitor cells describe what Stibo's public site and press releases say as of the date above. If we got something wrong, email support@myorg.ai. We will fix it, credited.

What matters	DataShield	Stibo Systems	Edge
Standing up the model	An agent does it with you. The project tool interviews a business user. It writes a plan from those answers plus live platform state. Then it walks a gate, step by step. Each step shows a what, why, impact and alternatives body. You confirm or reset it. A reset flows back through each linked choice. There is no accept-all button, on purpose. One single step then builds the entity types, trees, draft match setups, reference links and rules. Each gets marked with an honest gate state. The tool never promotes a setup on its own. It never runs matching on its own. It never skips the paired-gate test run. 15 commands, no setup fees.	A setup project. STEP is model-driven and the models run deep. Standing one up is a big job, though, usually with a partner attached. Third-party review sites put big MDM builds in the six to seven figure range. Stibo publishes no numbers itself. We found no guided interview or model-build tool shown in their public docs.	◆
Product MDM, PIM and syndication	None. No PIM, no digital asset store, no supplier onboarding, no GDSN, no channel syndication. Ontology has GTIN, MPN and CAS ID checks, plus product tree lookup (UNSPSC, GPC, ETIM, HS, INCI). That is not a PIM. We won't dress it up as one.	The core franchise, and thirty years deep. Product Experience Data Cloud. PIM. DAM. Syndication. Plus ProductGen AI, for made and localized product text with sign-off steps. Stibo's site says Hager Group runs 200,000+ products and 1.7M assets on it.	◇
Customer and party mastering	Fellegi-Sunter fuzzy record linking, with Jaro-Winkler, normalized Levenshtein, Soundex and Double Metaphone comparators. LSH blocking. Trained m/u odds on a frozen holdout. A trained polarity flip is a hard refusal. Five survivorship rules. 'Most trusted' reads measured overturn rates from stewardship, not a hand-ranked list. A top-ID tier routes ID conflicts to a human instead of blind-merging. Merge, unmerge, separate, defer and link are all first-class. Record locks, field pins, as-of rebuilds, and append-only version history survive deletion too. Population Stability Index drift watch flags a retrain. It never acts on its own. Batch and on-demand matching, not a sub-second stream engine. We won't pretend to be one.	Customer Experience Data Cloud: single customer view, address checks, real-time data quality, and MDM SmartSync for Salesforce. It offers search-before-create duplicate prevention and two-way golden-record sync. Mature and widely used. The underlying match algorithms are not public.	◆
Ingestion and binding into mastering	Six on-ramps: inline, URL, and batch ingest. Presigned object storage. Storage watch sources. A file repo. And a catalog link to a live PostgreSQL source. No rows leave it. Link a table to an entity type once. Mastering then stays fresh on a set schedule. Remaster rules can be auto, agent-review or steward-review. Partial loads mark removed source records stale, and flag updated ones for a fresh look. A weekly full pass cleans up deletes. A re-link with a changed column layout gets refused, not silently accepted. That is PostgreSQL today, not your whole estate. We are not an ETL product. We won't sell you one.	Connector and sign-up breadth is theirs. Supplier onboarding, channel syndication, GDSN. A native Microsoft Fabric link. MDM SmartSync for Salesforce. An Azure Marketplace listing since 2023.	◇
Multidomain modelling	An open entity-type list, with a People, Places and Things business group. That's a table row, not a fixed list. Three wired matching modes sit per type. Trees are parent-scoped. A child setup matches inside its parent's scope at a base threshold. Cross-parent, it matches at a stricter one. Live containment edges feed measured rollups. Links are directed, and carry valid-from and valid-to dates. Domains carry an owner and a rule set. You model your domain. You won't get a packaged Customer 360, supplier-onboarding or sustainability app. We won't ship you a template to bend.	Six packaged data clouds cover product, customer, business partner, supplier, location and sustainability. Industry add-ons and deep tree modelling sit behind them.	◇
Stewardship and earned automation	Stewards review patterns, not items. One call closes out a whole pattern. Proof backs it, plus a counter-check that keeps the step honest. A three-rung trust ladder controls automation. One human touch counts as one approval. Even when it closes 8,456 items. 50 approvals at a 98% rate, with zero pushback, promotes a rung. A single pushback demotes it. At the top rung, a fixed sampler routes 10% of auto-closed items to human audit. That way, you can prove why any item was picked. Standing rules start staged. They need a second release call. They auto-pause on an overturn. Blast-radius dry runs call the writer's own gate code. So a preview cannot say yes, then refuse.	Mature stewardship and control workflows sit inside STEP. Check rules and an audit trail nobody can edit, used at large firms for years. Their console has more road behind it than ours. Still, G2 reviewers score STEP's ease of use at 6.9 out of 10, below several category peers.	◈
Admission gate for agent reads	A golden record has to earn the right to be read by an agent. Six quality checks, with published weights and floors. Completeness, freshness, consistency, uniqueness, accuracy, conformity, and consent validity. A record is agent-ready only at a combined score of 0.70 or better. Each graded check must clear its floor, and a consent check must fail closed. One rule enforces that. Across both the SQL and the app read paths. It's never re-derived per path. Consent covers all six GDPR Art. 6(1) lawful bases across nine purposes, on an add-then-replace model. No recorded basis means no access. Reads come from views that mask by default. The reader role holds no grant on the base table. Accuracy and conformity score only where you have written check rules.	Data quality, checks and control rules. The MCP release says compliance controls and data rules stay intact as agents work within set limits. We found no public method for this. Nothing holds back a record until it clears a quality and consent bar.	◆
Audit evidence	A SHA-256 hash chain with Ed25519-signed checkpoints, themselves chained. Checking it returns clean, marked damage, or tampered. It names the failure: tampering, insertion, deletion or truncation. Re-tampering a marked-damaged chain un-marks it on its own. Inside MDM, each in-place control change writes a row. It shows before and after, in the same step. Try the verifier.	The MCP launch says AI decisions should be "explainable, auditable, and human-in-the-loop where required." STEP carries an audit trail nobody can edit. We found no public crypto tamper-proof method for agent or tool actions.	◆
Agent authorization	Each checked tool call passes a scope gate, a consented-tool allowlist, a set access gate. It gets a mid-session revocation re-check before dispatch, too. Then it's metered. Then it's sealed into an audit row. It fails closed. Cedar decides admin, config, token, role and vault questions, not the dispatch hot path. We say so plainly.	"Compliance controls and data rules remain intact as AI agents operate within defined parameters." That is the whole public statement. We could not find a per-call check point. No scope ceiling, no access model, in the announcement.	◆
Break-glass	Scoped, time-boxed emergency access for agents. Admin plus IP-allowlist plus step-up, gated, auto-revoking and fully audited. It cannot be quietly deleted from the log.	Not shown in their public docs.	◆
GDPR erasure	Crypto-shred: deleting the subject key destroys each copy of their data at once. This is cited to ISO/IEC 27040 and GDPR Art. 17. Actor IDs in the chain carry HMAC commitments, so the audit chain still checks out afterwards. ISO 27560 consent receipts get signed at grant and at withdrawal. On the MDM side, a removed golden leaves a tombstone. It records the reason and what came after. The change stream carries no field values at all, so there is nothing downstream to purge.	STEP has control workflows, check rules, and an audit trail. Say a subject asks for erasure. What happens to a golden record already synced downstream isn't shown publicly. Worth asking on the call.	◆
Tokenization and PII handling	Data gets tokenized at intake. Agents query tokenized data over MCP. Detokenizing is a special, logged step. Tokens are deterministic, join-preserving and vault-reversible, so mastering still works across sources. Derived phonetic and n-gram fields inherit their base field's PII verdict. A name cannot be rebuilt from its Soundex. A tokenized-at-rest matching field makes the run refuse with a typed error, rather than mega-merge. Plus 129 field classes for PII, PHI, financial data and secrets. It is done the same way every time, from one config digest.	Data quality, checks and control rules. Tokenization is not a word Stibo uses in public docs. We found no built-in PII or PHI classification library.	◆
MCP and agents	More than 200 MCP tools across Ontology, Auth, Corpus and Lighthouse. Mastering alone is 143 commands, about a third of the whole agent surface. It covers matching, stewardship and guided model build. MCP tool tokens carry scope ceilings. Delegation is RFC 8693 token exchange with an enforced ceiling. Per-call metering ties back to the agent. Goldens also reach agents as RAG grounding documents, built from the masked view. Chunks get hard-deleted when a record leaves the gate.	A real open MCP server, shipped 29 June 2026. It exposes the meaning, links and trees from the STEP graph. Platform-agnostic, with a Microsoft shopping-agent demo. Their surface is MDM-scoped. Ours spans mastering, catalog, classification and identity.	◈
Deployment	Self-hosted, in your own cloud or data center. Or a single-tenant server we run for you. Docker images cover Auth, Ontology, Corpus and Lighthouse. Guardian checks each one against a signed deploy manifest. Ed25519 audit-signing keys stay on your box, in a key folder you control. Rotation is kid-keyed, and it fails closed on an unknown key. KMS or HSM custody is a built-in seam in Auth, not a shipped link. HMAC tokenization keys sit in your setup today, or come from your machine key. Not in a KMS.	SaaS first, and winning at it. Stibo reports 77% of customers on SaaS as of June 2026. SaaS revenue is up 17%. On-prem and private setups get named in their docs. So does an Azure Marketplace listing since 2023, and a native Microsoft Fabric link.	◈
Maturity signals	Auth, Guardian and Lighthouse run live in production (Guardian and Lighthouse since April 2026). Entity resolution gets checked against roughly 370,000 real public records. Across three City of Chicago data sets, not only made-up ones. We publish the trap cases it clears. There is no record-count ceiling published. We won't invent one. SOC 2 isn't certified yet, and we say so.	Founded 1994, foundation-owned, roughly 600 to 840 staff across 18 offices. Stibo reports DKK 1.31B revenue in FY2026. They hold Gartner MQ Leader 2026 and Forrester Wave Leader Q2 2025. We cannot match any of that. We'd be lying if we tried.	◇
Pricing and time to value	Public model, scoped instant quote, no sales wall. Self-hosted. The guided build means no required build programme stands between you and a working draft model.	Quote only, priced by users, volume and modules. Third-party review sites put big MDM builds in the six to seven figure range. Stibo publishes no numbers itself.	◆

◆ DataShield leads◇ Stibo Systems leads◈ comparable

Stibo claims are drawn from stibosystems.com and Stibo Systems' own press releases, last checked 13 September 2026. Counts and financials are Stibo's own published numbers. Sources are linked below rather than recalled from memory.

Three things you get here that you won't get from an enterprise MDM suite

Proof that survives an audit

A log that can be quietly edited proves nothing. Ours is a hash chain with signed checkpoints. The verifier tells you what broke, not just that something did. That is the property EU AI Act Article 12 and HIPAA §164.312(b) reviewers care about. Try it in your browser, no signup.

Power that can change mid-flight

A steward resigns on a Friday. Their agent is 20 minutes into a 40-minute merge job against your customer golden records. With DataShield, the next checked tool call gets re-checked against current access. It fails closed. A suite with a nightly sync finds out on Monday. How Auth does it.

A model an agent builds with you

Most MDM buys start with a workshop and a partner. Ours starts with a conversation. An agent asks your business user what they run. It writes a plan. It puts each choice in front of you to confirm or reset. Then it writes the draft model in one save. Each match setup still has to train. It has to pass a frozen test run. Then get promoted, before it masters a thing. See the ontology.

Where Stibo Systems is genuinely stronger

Start with the obvious. Stibo has mastered product data since 1994. The company behind it dates to 1794. That makes our track record a rounding error. They are a Gartner Magic Quadrant Leader for MDM, as of April 2026. And a Forrester Wave Leader from Q2 2025. In June 2026 they reported a record year. Stibo says revenue hit DKK 1.31 billion. SaaS revenue rose 17%. 77% of customers now run SaaS. Their product side is a different weight class from ours. PIM, digital assets, supplier onboarding, syndication. ProductGen AI covers product content in many languages. If that is your problem, buy Stibo. Their June 2026 MCP server is real work, not a press release. It hands agents the semantics, links and trees from the STEP graph. They beat most of the MDM field to it.

They also have the bench we do not. 18 offices. A partner network. An owner with no exit to chase.

Here is the push-back, and it is narrow on purpose. Read what the MCP announcement promises about control. "Compliance controls and data rules remain intact as AI agents operate within defined parameters." We read that release closely. We could not find the mechanism under it. What decides a given call? What happens on the call right after you revoke an agent? Can you show an examiner that the March agent log was not edited? There is a fourth question the suites rarely invite: who builds the model? Stibo sells deep models plus a project to fit them to you. We let an agent run the interview. It puts each choice in front of you as a step you confirm or reset. It writes the draft model in one save. Nothing masters a record until a frozen test run goes green.

A thirty-year-old control suite should be able to answer the control questions in public. Until it does, an agent reading mastered customer records is running on trust. We would rather it ran on a scope ceiling. A revocation check. A quality gate. A signed chain.

Questions worth asking both of us

These are the questions we would ask if we were the ones signing. Put them to each vendor on your list, us included.

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

DataShield: yes. Each record commits to the one before it. Checkpoints get Ed25519-signed and chained. Checking tells deletion apart from truncation and from tampering. Run it against a sample chain at /verify. Stibo: STEP keeps an audit trail of data changes, and the MCP release calls agent decisions "auditable." We found no public tamper-proof method. Ask them to show one. Ask whether it covers agent tool calls or only record edits.

What happens to a revoked agent mid-session?

DataShield re-checks access on each checked tool call. Revocation lands on the very next call, and the context drops to anonymous. Stibo's MCP server says agents operate "within defined parameters." We could not find a revocation model in their public docs. Ask how long a compromised agent keeps reading your customer golden records after you pull its access.

How does GDPR erasure interact with the audit trail?

DataShield crypto-shreds the subject key. That destroys each copy of their data at once. It issues a signed ISO 27560 consent receipt. Actor IDs in the chain carry HMAC commitments. So the proof still checks out once the subject is gone. On the mastering side, a removed golden leaves a tombstone with the reason. Our change stream carries no field values, so there is nothing in it to purge. Stibo has control workflows and check rules. What happens to a golden record already synced downstream is the harder question. Ask for the mechanism, not the workflow.

Is DataShield a Stibo alternative for product data and PIM?

No. We have no PIM, no digital asset store, no syndication and no GDSN. Say the buying trigger is a product catalogue. Stibo, or one of its PIM rivals, is the right call. We will tell you that on the first call. Where we compete is customer and party mastering. Above all, when AI agents are going to read those records.

Stibo shipped an MCP server too. What's different?

Theirs, from June 2026, hands an agent the STEP semantic graph: entities, links, trees. It is a good design. It beat most of the MDM field to market. Ours is where the model gets built and the data gets queried. An agent can interview a business user. It works the decision gate and builds a draft model. Then it trains, tests and promotes the match setups. On the read side, the tool token carries a scope ceiling. The call gets authorized and metered before dispatch. The record has to clear a quality and consent gate first. PII comes back tokenized, unless detokenizing is clearly allowed. The step gets sealed into a chain. Score it even on the fact of shipping. Then ask each of us what the server refuses to do.

Does DataShield have SOC 2?

Not yet, and we won't imply otherwise. Auth runs live with a public threat model and a verifier anyone can run. Guardian and Lighthouse have run 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.

Stibo Systems launched an open MCP server on 29 June 2026, positioning "MDM as the active intelligence layer for the agentic enterprise" and stating "compliance controls and data policies remain intact as AI agents operate within defined parameters." - PR Newswire, 29 Jun 2026
Record fiscal year: DKK 1.31 billion revenue, up 6.0%; SaaS revenue up 17.0%; 18.1% EBITDA margin; 77% of customers on SaaS; growth in customer MDM led by financial services and pharma. - PR Newswire, 25 Jun 2026
Named a Leader in the 2026 Gartner Magic Quadrant for Master Data Management Solutions. - PR Newswire, 9 Apr 2026
MDM SmartSync for Salesforce: search-before-create duplicate prevention, real-time golden-record sync and bidirectional CRM integration for customer data. - PR Newswire, 25 Sep 2025
ProductGen AI: generative product content creation, governance and localization with human-in-the-loop approval before publishing. - PR Newswire, 30 Sep 2025
Named a Leader in The Forrester Wave for Master Data Management, Q2 2025. - Stibo Systems press release, Jun 2025
Current hero positioning: "Trustworthy Intelligence. Your AI is only as good as what you feed it," with six data clouds spanning product, customer, business partner, supplier, location and sustainability. Customer counts such as Hager Group's 200,000+ products and 1.7M assets are Stibo's own published figures. - stibosystems.com, 13 Sep 2026

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