Privacy & Compliance
You can only honor a person’s rights if you can find every record about them. The same person sits in your CRM, support desk, marketing tools and warehouse under different names and emails, and a search for one identifier finds only part of them.
For agents. Agents find every record about a person in one lookup, instead of searching each system by email.
Two systems answer the request. The third holds her data under another name and email.
Rights Belong To People. Data Belongs To Systems
Privacy requests, consent preferences and regulatory reports are all about people and entities: this customer, this consumer, this facility. The data about them is spread across systems that were never designed to agree on who is who.
So compliance work runs on searches. Someone looks up an email in the CRM, a customer number in billing and a phone number in support, and stitches the results together. Records under a different spelling, an old email or a married name are not found, and the gaps do not show.
Every process built on those searches inherits the gaps: requests that miss records, consent that disagrees between systems, and reports that do not reconcile with the audit.
Searches, Not Identities
Each system is searched for one identifier and returns only the records that use it.
Scattered Records
One person or entity is spread across CRM, support, marketing, billing and the warehouse.
Invisible Gaps
What was never found looks the same as what does not exist.
Resolve The Person Before The Request
Resolve people and entities across systems ahead of time, and give each one an identity that lists every record behind it. Then run privacy requests, consent and reporting from that identity instead of from a search.
The scope of each task becomes the whole person or entity. When records change, the identity is kept current, so the next request starts from complete data too.
Requests, consent and reports all start from this one identity.
One Identity Per Person
Every record about a person, whatever name or email it uses, is linked in advance.
Work From The Full List
Requests, consent and reports act on all of the records behind the identity.
Kept Current
New and changed records join the right identity as they arrive.
Every Obligation Starts With Finding The Person
GDPR Data Subject Requests
Find every record for a person across systems for access, rectification and erasure.
Learn moreCCPA Compliance
Honor California consumer requests across fragmented customer data.
Learn moreConsent & Retention
Apply consent and retention policies to the person, not to scattered rows.
Learn moreRegulatory Reporting
Report on resolved entities so filings and audits reconcile to one version of the truth.
Learn moreThe Identity Layer Under Privacy
Zingg runs as a workload inside your data platform and gives every entity one persistent ZINGG_ID. Everything above it reads the same resolved entities.
The same layer powersCustomer Analytics & MarketingFinancial Crime & RiskSupply Chain & ProcurementProduct 360Master Data ManagementAI & Data Foundations
What Zingg Brings
Persistent ZINGG_ID
Every resolved entity keeps one global ID across systems and runs. ZINGG_ID
AI Plus Rules
Matching learned from your labels, combined with deterministic rules where you have them. How Zingg matches
Incremental Flow
Only new and changed records are matched, and IDs persist. Incremental flow
In Your Data Platform
Runs on Databricks, Snowflake, Microsoft Fabric, Google Cloud or AWS. Data never leaves your account.
Privacy & Compliance Questions
Why is entity resolution needed for privacy compliance?
Because rights and obligations attach to people, while data is stored per system under different identifiers. Without resolving who is who, you cannot be sure you found every record.
Does Zingg make us compliant?
No tool does that on its own. Zingg resolves people and entities and lists every record behind each one, so your privacy, legal and reporting processes can work from complete data.
Does personal data leave our environment for matching?
No. Zingg runs inside your Databricks, Snowflake, Microsoft Fabric, Google Cloud or AWS account.
Can reviewers check why records were linked?
Yes. Explainability shows the evidence behind each match before anyone acts on it.
Start From The Whole Person
Resolve people and entities inside your own data platform, then build every privacy and compliance process on them.