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Fuse Platform

The data engine that orchestrates your information system

Fuse turns fragmented, unreliable data into information a business can act on. It ingests from many sources, validates, enriches, standardises and synchronises, and produces governed golden records that stay accurate in every system and every channel.

Bring one source and one record type you cannot trust.

Positioning

One pipeline, whatever the record is

Fuse was built for organisations managing complex product, customer, supplier and operational data: many sources, several owners, no single version anyone trusts.

The mechanics do not change with the subject. Ingest, map to a model, reconcile, control, enrich, govern, distribute. Product data for e-commerce is the configuration of that pipeline we sell today, and it is where the model, the locales and the identity rules already exist.

Capabilities

What the platform does

Each capability is configuration rather than code: you describe the model and the rules, and the pipeline runs them on every load.

  1. Ingestion

    APIs, files, feeds, extracts from enterprise systems and manual entry, all arriving in the same pipeline with the same controls.

  2. Intelligent schema mapping

    Fuse infers the structure of a new source, proposes a mapping to your target model and shows the result before any row is committed.

  3. Data quality workflows

    Deterministic cleanup first, then detection against your rules at the strictness you choose. Nothing is silently corrected.

  4. Golden records

    Field-level source assignment, priority rules between systems, conflict detection and version history, producing one governed record per entity.

  5. Synchronisation

    A projection per destination — ERP, PIM, MDM, WMS, e-commerce platform, marketplace or internal system — exported as soon as a change is validated, or on that destination's cadence.

  6. Traceability

    Origin, transformation and validation status on every field, so the answer to "where did this value come from" takes seconds.

  7. Exception management

    Everything that fails a rule or contradicts another source waits in the Inbox for a person to accept, adjust or reject.

People and agents

Agents accelerate the work. People set the rules.

Each agent has one job and a defined boundary. You choose which ones run, on which fields, and how strict they are.

  • Data Mapper

    Reads a source, proposes the mapping to your model and reports what it could not place.

  • Harmonizer

    Deterministic cleanup only: whitespace, number and date formats, GTIN shape, unit aliases, approved glossary terms.

  • Validator

    Detects and reports. Completeness, schema and business rules at your chosen strictness; it never rewrites the record.

  • Classifier

    Proposes a category against the taxonomy you provide, and says when it is unsure.

  • Translator

    Moves content into your configured locales and flags what is still untranslated.

  • Writer and Editor

    Draft and tighten commercial content from validated fields, following your brand rules.

  • Integrator

    Runs the import and export workflows, with success, error and retry per run.

  • Web Lookup

    Retrieve missing data for configured fields from approved external sources.

Architecture

Ports in, ports out, one governed core

Sources and destinations are adapters around a model you own. Adding a system means adding an adapter, not reshaping the core.

Domain

The product model itself. No framework, no database, no transport.

  • Product
  • Variant
  • Brand
  • Category
  • Organization
  • Offer
Use cases

What the platform does, expressed once and reused by every entry point.

  • Match
  • Normalise
  • Validate
  • Enrich
  • Govern
  • Publish
Ports

The interfaces the use cases depend on. Stable contracts, versioned.

  • Ingestion
  • Rules
  • Publication
  • Audit
Adapters

Replaceable implementations. Adding one does not touch anything inside.

  • CSV, JSON and XML files
  • REST APIs
  • Native and custom connectors
  • Object storage

Dependencies point inwards only. The domain has no knowledge of files, HTTP or any one system, which is why a new integration is an addition rather than a change.

Inbound
Files (CSV, TSV, Excel, JSON, XML), REST endpoints, native connectors, exchange standards such as FAB-DIS, ETIM xChange, BMEcat and GS1, and manual entry.
Outbound
The same protocols, or custom connectors, projected per destination: PIM, ERP, MDM, WMS, e-commerce platforms, marketplaces and internal systems.
Model
Entities, attributes, business keys, locales and priority rules, all configuration.
Environments
TEST and PROD. Validate a slice in TEST, then promote the workflow. Configuration changes are committed in TEST first.
Audit
Field-level origin, transformation, validation status and change history.
Residency
Product data is processed and stored in the European Union.

Who it serves

Less time fixing data, more time using it

  1. Business teams

    Decide on the exceptions that need a commercial judgement instead of rebuilding the catalogue in a spreadsheet.

  2. IT teams

    One mapping and one validation layer, instead of a point-to-point script per source and per destination.

  3. Data stewards

    Rules, source priorities and strictness in one place, with an audit trail on every field they are accountable for.

Where to start

E-commerce is the configuration we sell today

Fuse for e-commerce is this platform set up for a European product catalogue: entities, locales, currency, units and a GTIN-first identity rule ready on day one, with a flat SKU export for the shop or the PIM.

The Fuse for e-commerce page also sets out, in one place, where Fuse fits and where it does not.

Tell us which records nobody trusts

Product, supplier, customer or operational. Bring one source and the record type it feeds, and we will show you what the pipeline does with it.

Thirty minutes on your data, not a slide deck.