Fewer Custom Pipelines
Stop building per-partner parsers and per-format normalization scripts on Lambda, Step Functions, and EventBridge. The intake work lives in the platform that already moves the files.
Turn File Received Into Data Ready, Automatically
Integrations break the moment a file crosses a boundary from a partner, supplier, or legacy system. Files.com sits right there and makes the data inside the file usable the moment it lands. Extract the meaning out of what arrives, transform partner formats into your own schema, and verify it’s correct before anything downstream touches it. All at intake, in the same platform that already moves the files.
The Mess Starts Where Files Cross Boundaries
Partner data and EDI feeds are messy. Every partner reads the same standard a little differently, so the file you get rarely matches the spec. When a file crosses from a supplier, a partner, a subsidiary, or a legacy system into yours, the formats don’t line up. Your downstream systems inherit the mess. That’s where the broken data, the late files, and the constant cleanup come from.
Extract, Transform, Verify keeps that mess from spreading. It’s how Files.com goes from moving files to making the data inside them usable. Files.com doesn’t become an ETL product to do it. It does the work right where files arrive, before anything downstream sees them.
Three Steps From Arrival To Action
Each step is a real capability you can use on its own. Together they take a raw inbound file to clean, verified, routed data.
Extract: Read What Arrives
Read what arrives, whatever shape it takes. File extraction pulls field values out of structured files (XML, JSON, EDI, HL7, CSV) into metadata. AI handles the messy files that don’t fit a fixed shape. So fewer files get kicked to a human, and you act faster on every one.
Transform: Make It System-Ready
Normalize partner formats into your own schema with TransformScript. Reshape payloads, convert between interchange formats, standardize fields, enrich records, and route on content. A partner’s odd input becomes a predictable output your systems already know how to read.
Verify: Catch Problems Early
Check the data is correct before downstream systems ever see it. Define what “correct” looks like, catch broken documents early, and monitor delivery so a late or missing file raises an alert instead of slipping by unnoticed.
What You Get For Doing It At Intake
Doing extract, transform, and verify the moment a file lands pays off across every integration you run.
Fewer Downstream Failures
When bad data is caught and repaired at the moment it arrives, your downstream systems and your support team stop inheriting the mess.
Faster Partner Onboarding
A new partner’s quirky format gets normalized at intake instead of triggering a months-long integration project, so you onboard them in days.
Cleaner Audit And Observability
Because it all runs inside Files.com, every transform, extraction, and check is part of the same audit record. It’s not scattered across services you have to stitch together, so the security review has one place to look.
Go Deeper On Each Piece
The transform engine is Files TransformScript, a DataWeave-inspired language that reshapes, normalizes, and routes data inside your Automations. The extract engine is file extraction, which pulls field values out of structured files into metadata you can filter and route on.
Usage across all of it consumes Transformation and AI Credits, included per plan and scaling by tier. See what your plan includes on the pricing page.
Extract, Transform, And Verify: Common Questions
What teams ask about how Files.com makes inbound data usable at intake, how it differs from an ETL tool, and where AI fits in.
Make Inbound Data Usable The Moment It Lands
Start a free trial and build an Automation that extracts the fields you need, transforms the file into your schema, and verifies it. All before a downstream system ever sees it.
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