Get File Ingestion Logic
Out of Your Codebase
Embed a white-label import portal into your SaaS. Your team manages transformation templates in DataFlowMapper — no deploys when a client's format changes.
Custom engagement — scoped, configured, and launched with your team
Recurring imports shouldn't be a recurring engineering problem.
Format Changes Become Engineering Tickets
A renamed column, a new field, a client that exports slightly differently — each one routes to your engineering queue. Triaged, coded, tested, released. While your client waits on month-end processing.
Clients Build Workarounds That Break
Blocked imports push clients toward Excel macros and manual edits. Files grow large enough that macros stop working. Data reaches your product with silent errors introduced before it ever touched your ingestion layer.
Import Logic Compounds With Every Client
Each new format adds code. No shared place to audit, version, or reuse it when the next similar client arrives. The logic is scattered and the institutional knowledge lives in someone's head.
Built For
SaaS platforms with recurring, operational client data imports
Instead of rewriting ingestion paths, DataFlowMapper centralizes mapping, validation, and transformation logic into a managed layer your product calls.
How It Works
Set it up once. Your clients run it forever.
Your team authors the rules. Your clients own the import step. No transformation logic lives in your codebase.
Your Team Builds the Templates
Define destination fields, mapping rules, and validation logic in DataFlowMapper — with AI assistance if needed. Update any template instantly. No deployment, no ticket.
Client Uploads a File
The portal auto-matches the upload against your template library. For new or unrecognized formats, AI generates a mapping your team reviews before it's exposed to clients.
Review, Validate, and Submit
Transformation errors surface in a validation grid. Once the data passes, the client submits — and it routes to your S3 bucket or import endpoint, governed by the rules you set.
Your Controls
You Configure It. Your Clients Run It.
The portal surfaces only what you define. Clients interact with your rules — they never see or touch how the transformation works.
Template Library
Build and version format definitions in DataFlowMapper. Changes go live immediately — no deployment cycle, no release window, no ticket.
Governance Mode
Configure per-session whether clients publish directly to production or route through your internal review queue first.
Data Destination
Processed files route to your S3 bucket on submission. API and database destinations are available and scoped during onboarding.
Client Authentication
Clients authenticate through your own product using your user IDs. No DataFlowMapper accounts or new login flows required.
AI-Assisted Mapping
When a new client format arrives, AI generates a mapping. Your governance model determines whether these templates need review before surfacing to the client.
Import Type Scoping
Restrict the portal to templates for a specific workflow. One integration can serve multiple import types — configured at session init.
Comparison
Why Teams Choose This Over the Alternatives
There are three common paths to client-facing data imports. Each has real tradeoffs worth understanding.
Custom development
Building In-House
- –6-12 months of engineering to launch
- –You own every maintenance decision
- –Format changes require code changes and a release
- –Import logic scattered across the codebase
- –No reuse across similar client formats
- –Support burden scales with client volume
Client upload widgets
Flatfile, Dromo & Similar
- ✓Handles basic column mapping and cleaning
- –Transform rules require developer configuration
- –Limited support for reusable complex transformation logic
- –Format changes still route through your dev team
- –Designed for one-time onboarding, not recurring operational imports
- –No internal review or governance workflow
Custom engagement
DataFlowMapper Portal
- ✓Live in weeks, not months
- ✓Full transformation logic — no dev involvement per format
- ✓Template updates with no deployment
- ✓AI-assisted mapping for new client formats
- ✓Built for recurring operational imports
- ✓Per-session governance and review controls
How We Work Together
This Is a Custom Engagement
We scope, configure, and launch with your team. The implementation is specific to your product, your templates, and your clients.
We Scope Together
We review your import formats, governance requirements, and client use cases to build the integration plan specific to your product.
We Configure and Test
We set up your template library, configure the portal, and run end-to-end tests with your team before any client touches it.
Your Team Manages It
Format changes become template updates in DataFlowMapper — not engineering tickets. Your clients import on their own schedule.
Ready to explore it for your product?
Scoped as a fixed engagement
The visual data transformation platform that lets implementation teams deliver faster, without writing code.
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