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Master Data Management · multi-domain

One trusted record. Across every system.

Unify fragmented enterprise data through matching, merging, survivorship, governance and cross-domain relationships. Autonera establishes trusted master records while autonomous operations continuously find and resolve inconsistencies — inside approval boundaries you set.

Walk one supplier through resolution. Use Next, or jump to any stage.

Resolution workspace · Supplier domain

Three systems describe a supplier called Hollister. Names, addresses and identifiers disagree. Highlighted values conflict with at least one other source.

ERP · East instanceVND-004417
Legal name
HOLLISTER FLUID CTRL INC
DUNS
08-412-7739
Tax ID
34-1987265
Address
1180 Kestrel Pkwy, Toledo OH
Country
US
Website
empty
Payment terms
Net 45
Category
Valves

Last updated 2023-11-02

PIM · Manufacturer masterMFR-2291
Legal name
Hollister Fluid Controls, Inc.
DUNS
empty
Tax ID
34-1987265
Address
1180 Kestrel Parkway, Suite 200, Toledo, OH 43615
Country
United States
Website
hollisterfluid.com
Payment terms
empty
Category
Industrial valves & actuators

Last updated 2025-03-18

Supplier portal · OnboardingSUP-77810
Legal name
Hollister Fluid Ctrls de Mexico
DUNS
81-266-0453
Tax ID
HFC990312K4
Address
Av. Ruiz Cortines 2410, Monterrey NL
Country
MX
Website
hollisterfluid.com
Payment terms
Net 30
Category
Valves

Last updated 2025-05-06

Stage 1 of 5 · Source records

Area A

Every domain on one model

Product, supplier, customer, location, asset and reference data share the same matching, survivorship and stewardship machinery. Relationships between domains are governed, not copied.

  • Product
  • Supplier
  • Customer
  • Location
  • Asset
  • Reference data
  • Cross-domain relationships
Shared modelrules, survivorship, stewardship

Supplier domain

Supplier entity

Hollister Fluid Controls, Inc.

Governed relationships

supplies Product, parent of subsidiaries

Area B

Match rules you can read

Match logic is configuration, not a black box. Each rule declares its fields, its method and what a match is allowed to trigger. Uncertain matches go to people.

  • Exact matching
  • Fuzzy matching
  • Duplicate detection
  • Match confidence
  • Configurable match rules
  • Entity resolution
  • Merge policies
  • Human review of uncertain matches
RuleComparesMethodMerge policy
Supplier · tax identityTax ID + countryExactAuto-merge under policy
Supplier · name and addressLegal name, street, postal codeFuzzy + normalizedScore, route by threshold
Product · manufacturer partMfr name + MPN, punctuation strippedNormalized exactAuto-merge under policy
Product · descriptionShort description, key dimensionsFuzzyAlways steward review
Customer · siteAccount name, ship-to geocodeFuzzy + geo radiusScore, route by threshold
Confidence routing
Below 0.65 · not a candidate
0.65 – 0.90 · steward review
Policy merge

Thresholds are set per rule and domain by stewards. A policy merge still requires every mandatory exact signal; otherwise it drops to review.

Area C

Golden records that remember where they came from

Survivorship works attribute by attribute with source priorities. Every contributing record stays cross-referenced, and every merge can be inspected and unmerged.

  • Golden-record creation
  • Attribute-level survivorship
  • Source system priorities
  • Source cross-references
  • Record consolidation
  • Merge history
  • Unmerge and correction

Source priority by attribute

Attribute1st2nd3rd
Payment termsERPPortal—
Legal nameRegistryPIMERP
WeightPIMSupplierERP
Country of originSupplierPIMERP

Merge history · GR-118204

  1. Created

    Consolidated ERP VND-004417 and PIM MFR-2291

  2. Linked

    SUP-77810 attached as subsidiary after steward approval

  3. Correctable

    Any contributor can be unmerged; its identity and source values are restored and the change is audited.

Area D

Reference data and hierarchies as governed structure

Controlled vocabularies standardize what gets compared. Hierarchies express parents, subsidiaries, sites and product structures so relationships survive consolidation.

  • Reference data management
  • Controlled vocabularies
  • Data standardization
  • Entity hierarchies
  • Cross-domain relationships

Supplier hierarchy

Hollister Fluid Controls, Inc. GR-118204

  • Hollister Fluid Ctrls de Mexico Subsidiary
  • Plant TOL-1, Toledo Location
  • Remit-to: Hollister AR, Cleveland Site

Standardization before matching

  • PCS, EA, eachEA
  • US, USA, United StatesUS
  • Pkwy, ParkwayPKWY
  • Ctrl Inc, Controls, Inc.CONTROLS INC
  • SS316, 316 StainlessStainless steel 316

Area E

Stewardship with a real queue

Data quality checks, validation and approvals produce exceptions with owners. Lineage and audit trails show who or what changed each value, and why.

  • Data quality
  • Validation
  • Approvals
  • Stewardship
  • Lineage
  • Audit trails
  • Exception management
Exception queue
  • EX-3104Uncertain matchHollister Fluid Ctrls de Mexico vs Hollister Fluid ControlsOwner: Procurement steward2h
  • EX-3097ValidationDUNS checksum failed on SUP-77422Owner: Supplier data team6h
  • EX-3091Survivorship tieTwo validated addresses, same date, Grainfield PumpsOwner: Procurement steward1d
  • EX-3088Reference driftUoM 'PCS' not in controlled list (12 products)Owner: Reference data owner1d

Autonomous execution

Agents carry the matching workload. Policy and people hold the boundary.

Nothing is merged just because an agent thinks it should be. Every proposal carries its evidence, and anything outside policy waits for a steward.

Agents propose

  • Detect likely duplicates as records arrive
  • Propose match groups with the signals behind each score
  • Evaluate conflicts and recommend survivorship values
  • Route uncertain cases to the owning steward
Approval boundary

People decide

  • Stewards own match thresholds and survivorship rules
  • Merges below threshold or with conflicts require approval
  • Any merge can be reviewed and unmerged
  • Every decision is attributed and retained as evidence

Buyer questions

What domains can Autonera manage?

Autonera is designed for multi-domain master data: product, supplier, customer, location, asset and reference data, with relationships between them governed together. Confirm domain coverage for your use case with our team.

How does match and merge work?

Records are first standardized, then compared with configurable rules across identifiers and attributes. Each candidate group receives a match confidence with the signals that produced it. Merge policies decide what happens next: high-confidence groups can merge under policy, uncertain groups go to a steward, and nothing below threshold merges silently.

Does Autonera support fuzzy matching?

Yes. Fuzzy comparison of names, addresses and descriptions is combined with exact and normalized matching on identifiers such as tax IDs, DUNS or manufacturer part numbers. Specific algorithms and tuning options are subject to product confirmation.

How are survivorship rules applied?

Per attribute. A rule can prefer a source system, the most recent validated value, the most complete value, or a standardized reference value. The golden record shows which source and rule supplied each value.

Can source identities be preserved?

Yes. Every golden record keeps cross-references to each contributing source record and key, so ERP, PIM and supplier systems can still find their own record.

Can incorrect merges be reversed?

Merge history is retained so a steward can unmerge a contributing record and restore its identity, with the correction recorded in the audit trail. Limits on unmerge after downstream publication are pending product confirmation.

How does MDM work with existing ERP and PIM systems?

Autonera can run alongside existing ERP and PIM systems, consuming their records and returning golden records and cross-references, or serve as the complete master data environment. Both are valid long-term choices.

Your next step

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