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TellParrot for Manufacturing

Material, supplier and equipment masters you can build on

Duplicate materials, inconsistent supplier records and drifting equipment data quietly tax every plant. TellParrot masters the records your ERP, MES and procurement systems disagree on.

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The problems we solve for manufacturing teams

Duplicate material masters multiply inventory

The problem

The same part exists under five codes across plants. Purchasing can't consolidate spend, inventory duplicates, and engineers reinvent parts that already exist.

How TellParrot solves it

Attribute-based matching (token, fuzzy and exact rules across descriptions, codes and specifications) surfaces duplicate material clusters at catalog scale for steward-approved consolidation.

→ A consolidated material master and the spend leverage that comes with it.

Supplier records fragment procurement

The problem

Each plant onboards vendors independently. One supplier appears a dozen times with different terms — risk exposure and negotiating power both suffer.

How TellParrot solves it

Supplier golden records resolve entities across ERPs with survivorship rules selecting the authoritative value per field; the knowledge graph relates suppliers to materials, sites and contracts.

→ One supplier view for negotiation, risk and compliance.

Equipment data drifts from reality

The problem

Asset registers lag field changes; maintenance planning runs on records nobody fully trusts.

How TellParrot solves it

Continuous ingest from maintenance and MES systems feeds equipment golden records, with quality rules and AI agents flagging stale, incomplete or contradictory entries — worst first.

→ Maintenance decisions on data that matches the plant floor.

Migrations stall on dirty data

The problem

ERP consolidations and system migrations blow out because nobody trusts the source data enough to cut over.

How TellParrot solves it

TellParrot ingests legacy catalogs, deduplicates and standardises them with cleaning projects and rules, and exports migration-ready golden records with full lineage back to the originals.

→ Cut-over datasets that are clean, mapped and auditable.

How TellParrot masters materials, suppliers and equipment

ERP, MES and procurement disagree on the records that matter — TellParrot consolidates them into masters you can build on.

Source systems
ERP (plant A)
ERP (plant B)
MES
Procurement
ingest & match
TellParrot
platform
One governed platform
Ingest & map
Match & merge
Govern & catalog
AI governance
governed exports
Consumers
Purchasing
Engineering
Maintenance
Migration / cut-over
One material, supplier and equipment master — spend leverage and maintenance decisions on data that matches the floor.

Capabilities doing the work

Material master deduplicationSupplier golden recordsCleaning projects & transform rulesEquipment data qualityMigration-ready governed exportsKnowledge graph relations

Duplicate materials consolidated, mapped back to every code

Attribute-based matching surfaces duplicates across plants; the golden material maps back to each local code — the platform's material master.

app.tellparrot.com/mfg/golden-records/mat-70155
Golden Records
Matching
Cleaning
Transform Rules
Lineage

Material · Bearing 6205-2RS

5 codes mergedDQ 97%Spec verified

Consolidated from 5 plant codes · mapped back to each

5
Plant codes
97%
Data quality
1
Golden SKU
PlantLocal codeDescriptionMapped
Plant ABRG-6205Bearing 6205 2RS✓
Plant B6205RSBall bearing 6205✓
Plant CB-62052RSBrg 6205-2RS✓
Plant D205BRGBearing dbl seal✓
Approve consolidationExport to ERP

Frequently asked questions

Can TellParrot match on technical attributes, not just names?

Yes — match rules are field-by-field with per-field weights and thresholds, so you can match on specifications, dimensions, codes and descriptions together, and require specific fields to corroborate before a merge is possible.

We run Business Central — does TellParrot integrate?

Yes, natively: ingestion from Microsoft systems including Business Central and Dynamics 365/Dataverse, plus governed export back to them and to Microsoft Fabric.

How do cleaning projects work?

Cleaning projects capture every field-level change as reviewable diffs, and the fixes can be promoted to transform rules that apply automatically to future ingests — so the same problem never returns.

Related industries

Wholesale & DistributionMining & ResourcesLogistics & Supply Chain

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