Where did the data change?

Trace supplier data from source to destination.

FileFresh is being built for teams that depend on supplier XML, CSV, API and inventory feeds — and need to understand whether bad data originated at the source or changed somewhere during the import.

Talk to us Tell us about your workflow

Product: FileFresh
Status: Early-stage product — currently in customer discovery
Looking at: Supplier XML, CSV, API and inventory feeds
Contact: ilya@filefresh.net

Supplier (XML · CSV · API) → Import / mapping (importer · mapping rules · middleware) → Destination (Shopify · ERP · WMS · Marketplace). Unresolved between supplier and import / mapping (changed here?); unresolved between import / mapping and destination (or here?).

Source
System or step
Destination
Data path
Unresolved: value differs, origin unknown
Traced: matches what arrived

Drawing: Supplier data, source to destination
Type: Conceptual illustration — not a product screenshot
Values: Invented examples

The sync succeeded.
The data still looks wrong.

A successful sync only tells you that a process completed. It does not necessarily tell you:

Whether the supplier sent complete data
Whether the source structure changed
Whether mapping behaved differently
Whether a field disappeared during transformation
Where an incorrect downstream value first appeared

Source (upstream) → Import (in transit) → Destination (downstream). Unresolved between source and import; unresolved between import and destination.

✓ completed is what each step reports about itself.

Traced against the source: nothing on this path.

Seeing that something is wrong is one problem.
Understanding where it became wrong is another.

Supplier data rarely follows a simple path.

Modern commerce teams often depend on several independent tools and suppliers — each with its own logs, formats and definition of “done”.

Supplier A (source) → XML (feed) → Shopify importer (importer) → Store (destination). Unresolved between shopify importer and store (stock 14 → 0).
Supplier B (source) → CSV (feed) → Middleware (transform) → ERP (system) → Shopify (destination). Unresolved between middleware and erp (variants 4 → 3).
Supplier C (source) → API (feed) → WMS (system) → Marketplace (destination). Unresolved between api and wms (<item> → <product>).

Where each unresolved segment sits is invented for illustration. In practice, finding that position is the hard part.

Drawing: Three supplier paths
Type: Conceptual illustration — not a product screenshot
Values: Invented examples, not customer data

Many tools, many owners. Suppliers, importers, middleware and destinations are often run by different teams or vendors.

Every step says “success”. Each system may correctly report that its own step succeeded while the final data is still unexpected.

The full path is the gap. FileFresh is being explored as a way to understand the complete path without replacing every system in it.

What we keep seeing

Patterns we’ve found while researching real supplier-data workflows. These are observations from discovery — not customer stories.

Source: Our discovery research
Type: Research observations — not customer stories
Examples: Illustrative values

Pattern	Example of the difference	What we’ve seen
Stock mismatches	upstream 14store 0	A store can show an item unavailable even when inventory exists upstream.
Import surprises	4 variants3 variants	Product fields or variants may not appear downstream as expected.
Supplier changes	<item><product>	A new supplier or changed product structure can create unexpected integration behavior.
Custom feeds	auth · custom mapping · edge cases	CSV/XML feeds may require authentication, custom mapping or special handling.
High-frequency data	refreshed every few minutes	Some operations refresh supplier inventory every few minutes, making reliability increasingly important.

These situations do not necessarily mean the supplier feed is broken. The difficult part is determining where the discrepancy began.

A clearer view between source and destination.

FileFresh is being designed around a simple idea: capture enough context around the data pipeline to make investigation easier when something looks wrong.

Instead of immediately replacing the importer or sync system, the goal is to help answer better questions.

What arrived?: What did the supplier actually send?
at the source
What changed?: Which values or structures changed compared with what was expected or previously received?
between deliveries
Where?: Was the difference already present upstream, or did it appear later in the pipeline?
along the path
When?: When did the behavior first change?
over time

Supplier (what arrived) → Feed (XML · CSV · API) → Import / mapping (in transit) → Destination (where it shows up). Traced from supplier to feed; traced from feed to import / mapping; unresolved between import / mapping and destination (variants 4 → 3).

Illustration of the “where?” question: the value matches what arrived until one transition, and that transition is the one worth investigating.

Drawing: Where a difference first appears
Type: Product direction — not a list of currently released features
Values: Invented examples

Keep your existing importer.

FileFresh is not intended to become another catalog importer. Your existing workflow may already handle synchronization very well.

The product direction is to make it easier to investigate what happened when the result does not match expectations.

Supplier (source) → Feed (XML · CSV · API) → Existing importer / middleware (unchanged) → Destination (Shopify · ERP · WMS).

Your tools keep doing the sync. FileFresh aims to add context.

Drawing: Alongside an existing workflow
Type: Product direction — not a released integration

Formats and systems in the workflows we’re researching

XML
CSV
API
FTP
SFTP
ERP
WMS
Shopify
Marketplace

Teams that depend on someone else’s data.

We’re currently speaking with teams where external product and inventory data directly affects what gets sold, shipped and shown.

Team	Where they meet supplier data	On the map
Ecommerce	Stores importing supplier catalogs, variants, pricing and inventory.	destination
Operations	Teams whose fulfillment and availability depend on external product data.	downstream
Marketplaces	Businesses combining product information from many suppliers or sellers.	many sources
Integration teams	Teams moving catalog and inventory data between ecommerce, ERP, OMS and WMS systems.	in transit

When something looks wrong, how do you find the source?

We’re currently speaking with ecommerce and operations teams that rely on external product or inventory data.

We want to understand how teams investigate supplier-data problems today before deciding exactly what FileFresh should become.

No sales deck required. We’re interested in understanding the workflow first.

Or write directly: ilya@filefresh.net

FAQ

FileFresh is early. If your question isn’t here, ask us directly.

What is FileFresh?

FileFresh is an early-stage product being explored around visibility and traceability in supplier-data workflows.

Is FileFresh another feed importer?

No. The current direction is to work alongside existing import and synchronization systems rather than replace them.

What types of data are you looking at?

We’re currently researching workflows involving XML, CSV, APIs, FTP/SFTP, inventory feeds and similar supplier-data sources.

Does FileFresh automatically fix bad feeds?

No. The current focus is understanding the visibility and investigation problem first.

Is FileFresh available today?

We’re currently in customer discovery and early product development. If supplier data is operationally important to your business, we’d like to talk.

Do I need to replace my existing integration?

That is not the current product direction. FileFresh is being explored as a complementary layer around existing workflows.

We’re building FileFresh around a simple question:

What did the supplier send — and where did the result begin to differ?

Talk to us

Tell us how supplier data reaches your business today.