One customer. One record.
Every system.
Golten resolves, merges, and governs entity data across every system — so your AI agents work with records they can trust.
Illustrative example. All names, contact details, identifiers, scores and account data shown are fictitious and do not represent any real person, customer or record.
Your data is fragmented. Your AI doesn't know it yet.
of enterprises have duplicate customer records across their source systems
average annual cost of poor data quality per organization
typical implementation timeline for legacy MDM platforms
From raw data to golden record in three stages
Ingest
Connect any source system — CRM, ERP, data warehouse — via API or real-time stream. Zero-config schema detection.
Resolve
AI entity resolution matches, merges, and scores records with 99.7% accuracy. Domain-pretrained models, not generic ML.
Activate
Golden records are instantly available for AI agents, analytics dashboards, risk engines, and compliance vaults.
Connects to the systems you already run.
Four ways in, one pipeline. Every record goes through the same cleanup, matching and merge steps, whichever way it arrives.
Push records from any application. Each source gets its own revocable key.
Every insert and update streams from the source database as it happens.
Scheduled pulls from operational databases, no agent to install.
Consume entity events straight from your message bus.
Golten- 1Cleanup
- 2Match
- 3Merge & survive
Query any mastered entity on demand.
Downstream systems receive every update as it lands.
Customer OntologyHow each customer engages with every product, account and household, in business context.
Customer Ontology: See how every customer connects to what they own.
The customer ontology shows how each customer engages with your business: the products they hold, the accounts they share, and the people and places they are connected to. In this fictional example, Sarah and David are both customers of Bank of XYZ, a made-up institution. Each holds a savings account, a checking account, and a credit card, and together they share a joint checking account, a joint savings account, and a mortgage on their home.
Illustrative example. Bank of XYZ is a fictitious institution, and the people, household, address, accounts and products shown are made up. The graph does not depict the operations, products or customers of any real bank.
Why Golten wins
Built for data engineers who ship, not consultants who configure.
Data Integration
Connect sources by API, file, database pull, change data capture or event stream. Every record goes through the same cleanup, matching and merge steps.
Versioned Rules
Test, preview and re-apply. Survivorship policies are published as numbered versions, and every change can be brought to existing records in one job.
Traceability
Every value on every golden record can be explained to an auditor, with field-level lineage and an append-only audit trail in your own database.
Self-host in Your Azure Tenant
Your data never leaves your environment. Deploy on AKS with workload identity federation.
Entity-Level SLAs
Data with a warranty. Monitor freshness, accuracy, and completeness per entity — not per pipeline.
MCP-Native Server
AI agents speak Golten natively via Model Context Protocol. No middleware, no adapters.
Built for scale.
Measured in milliseconds.
At 10 million records, Golten serves a golden record in under 7 ms and finds matches about 25× faster than leading MDM platforms' published figures