Supplier Product Data Onboarding Software

Onboard supplier product data without the manual cleanup

Supplier product information rarely arrives in the format your systems expect. Docxi.ai helps distributors, manufacturers, retailers, and marketplaces transform supplier PDFs, datasheets, spreadsheets, scans, and mixed catalog packages into structured, validated, publish-ready product data.

Start with one supplier catalog. We’ll help you identify where manual effort, data-quality risk, and onboarding delays are occurring.

Why it's hard

Your PIM can store product data. Getting it in is still painful.

Product information often reaches your team through email attachments, spreadsheets, technical datasheets, scanned catalogs, and supplier websites. Before that information can enter your PIM, ERP, ecommerce platform, or marketplace, someone still has to interpret, organize, map, and validate it.

  • Inconsistent file formats

    Suppliers use different file formats, attribute structures, and naming conventions.

  • Missing or inconsistent labels

    Required attributes are missing, mislabeled, or buried in unstructured paragraphs.

  • Multiple product types in one file

    A single catalog submission contains several distinct product families and taxonomies.

  • Cross-page attribute distribution

    One product’s specifications, dimensions, and compliance details span multiple pages.

  • Complex technical spec tables

    Specifications appear in nested matrices, engineering diagrams, or low-res scans.

  • Multiple schema requirements

    Different product categories require strict, distinct attribute schemas and rules.

  • Repeated manual re-mapping

    Catalog teams repeatedly map the exact same supplier format month after month.

  • Downstream catalog errors

    Quality errors and duplicate SKUs are discovered only after data enters live systems.

Complete Workflow

Supplier data onboarding is more than importing a file

Docxi.ai helps automate the repetitive parts while keeping your team in control of decisions that require judgment.

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1. Collect Files

Collect raw supplier files, datasheets, or feeds.

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2. Identify Context

Identify supplier identity and document context.

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3. Detect Groups

Detect product boundaries and logical groups.

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4. Field Mapping

Map supplier fields to internal data model.

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5. Assign Schemas

Assign category taxonomy and attribute schemas.

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6. Value Normalization

Normalize units, formats, and value lists.

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7. Business Validation

Run automated rule checks and completeness checks.

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8. Exception Review

Route uncertain or conflicting items for review.

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9. Record Approval

Approve clean records with visual evidence.

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10. PIM Publication

Publish structured data to PIM, ERP, or store.

What Docxi Does

An intake and quality layer before your PIM or ERP

We transform messy supplier content into structured, validated, and publish-ready product data — before it reaches your PIM or ERP.

Automatic Supplier Identification

Recognizes returning suppliers and loads saved mapping templates.

Simple & Composite Ingestion

Handles single-family datasheets or complex multi-product catalogs.

Multi-Page Product Correlation

Connects specs and dimensions scattered across catalog pages.

Dynamic Schema Assignment

Assigns appropriate schemas per product type dynamically.

Field-Level Source Evidence

Preserves page numbers and visual bounding boxes for every value.

Exception-Based Workflows

Routes low-confidence data to human reviewers for fast verification.

Supported Formats

Start with the supplier files you already have

You do not need to ask every supplier to reformat their data before you can begin. Docxi.ai works directly with the raw source material available to your team.

PDF CatalogsMulti-page brand & product catalogs
Technical DatasheetsEngineering & spec sheet documents
Scans & ImagesScanned paper docs & diagram images
Excel & CSVInconsistent supplier spreadsheets
Spec SheetsProduct specification documents
ZIP PackagesBundles containing multiple file types
Mixed PackagesPDFs, specs, images, & certificates
500+ Page CatalogsLarge multi-family industrial books

Intake Workflows

One workflow for simple files. Another for mixed catalogs.

Standard Ingestion

Simple Intake

Used when the submission contains one product family, one taxonomy branch, one known schema, and a consistent document structure.

Upload → Identify → Assign Schema → Extract → Validate → Approve

Complex Packages

Composite Intake

Used when submissions contain multiple product families, different taxonomies, mixed PDFs, technical specs, and supporting certificates.

Upload → Split Groups → Classify → Assign Schemas → Extract → Validate → Approve

Schema Mapping

Different products need different structures

A single supplier package may contain motors, sensors, gearboxes, valves, or control modules. Docxi.ai assigns category-specific attribute schemas dynamically.

Product TypeExample Schema Fields Extracted
Electric MotorVoltage, frequency, rated power (kW/HP), speed (RPM), frame size
Temperature SensorMeasurement range, accuracy, output signal (4-20mA), operating temp
Industrial GearboxGear ratio, output torque, max input speed, mounting orientation

Quality Assurance

Find problems before they reach your catalog

Extraction is only the first step. Docxi.ai validates every record against pre-defined rules before publication.

Missing Required Fields

Flag records missing mandatory PIM attributes.

Unit & Format Errors

Normalize imperial vs metric units and format rules.

Out-of-Range Values

Catch technical specs outside engineering thresholds.

Duplicate SKUs / MPNs

Detect duplicate identifiers across supplier submissions.

Cross-Page Conflicts

Reconcile conflicting values extracted from different pages.

Controlled Value Checks

Enforce allowed enum values (e.g. approved color lists).

Use Cases

Where supplier-data onboarding creates the most work

New Supplier Onboarding

Process new supplier catalogs, assign schemas, and prepare data rapidly.

Large Catalog Processing

Ingest multi-hundred page PDF catalogs with complex multi-family lines.

Mixed Supplier Packages

Extract data from ZIP bundles containing PDFs, Excel, spec sheets, & images.

Catalog Refresh

Compare updated supplier submissions with live data to extract only changes.

PIM / ERP Migration

Clean and structure legacy supplier data prior to major system migration.

Technical Digitization

Turn engineering PDF datasheets into structured, searchable SKU specs.

“Your PIM manages the product catalog. Docxi.ai helps make the supplier data ready for it.”

Docxi.ai sits upstream of your PIM, handling complex multi-page documents, multi-schema routing, and field-level evidence.

Frequently Asked Questions

Everything you need to know about supplier product-data onboarding, PIM preparation, and automated quality checks.

What is supplier product-data onboarding?

Supplier product-data onboarding is the process of collecting product information from suppliers, mapping it to an internal structure, normalizing values, validating the result, and preparing it for a PIM, ERP, ecommerce platform, or marketplace.

What types of supplier files can Docxi.ai process?

The platform is designed for PDFs, technical datasheets, spreadsheets, scans, product catalogs, and ZIP packages containing multiple file types.

Can one catalog contain multiple product types?

Yes. A composite intake flow can separate product groups, assign different taxonomy branches and schemas, and process each group independently.

Can one product’s data be spread across multiple pages?

Yes. Product information can be correlated across pages using identifiers, context, layout continuity, and related evidence.

Is Docxi.ai a PIM?

No. Docxi.ai is an intake and product-data quality layer that prepares supplier information before it enters a PIM, ERP, or other downstream system.

Does the system replace our catalog team?

No. It reduces repetitive extraction and cleanup work. Your team remains responsible for reviewing exceptions, approving important decisions, and managing data quality.

Can supplier templates be reused?

Yes. Approved supplier mappings, schema assignments, validation rules, and document patterns can be reused for future submissions.

How is extracted data validated?

Validation can check required fields, data types, units, controlled values, ranges, duplicate identifiers, taxonomy assignments, and conflicts across sources.

Can we trace a product attribute back to the source?

Yes. The platform is designed to preserve source file, page, evidence region, confidence, schema, and review information for extracted fields.

Can Docxi.ai work with our existing PIM or ERP?

Yes. The platform is designed to export structured, approved data through files, APIs, custom mappings, or other integration methods.

Get started

Start with a catalog health review

We begin with a consultative review of your current supplier onboarding process. No commitment, no sales pitch — just practical insights.

Review a sample supplier catalogIdentify manual effort and quality risksEstimate onboarding time and error ratesProvide a short improvement reportDiscuss whether a pilot makes sense