Clean up and validate incoming data before it hits your systems

Automatically catches incoming records, fixes formatting problems, and checks for missing fields before you use the data.

How the work actually flows

It branches. Exactly one path is taken; runs once per each incoming record.

Pattern: Exclusive Choice (4) · Multiple Instances with a priori Run-Time Knowledge (14)

flowchart TD trig>"partner sends data batch"]:::trig s0[["rename fields to match"]]:::mi s1["convert dates and formats"]:::task s2["fill missing default values"]:::task s3["flag incomplete records"]:::task trig --> s0 s0 --> s1 s1 --> s2 s2 --> s3 gx{"× required fields complete"}:::gate s3 --> gx p00["mark as clean"]:::task gx -->|"complete record"| p00 p10["add to error report"]:::task gx -->|"missing fields"| p10 p00 --> out p10 --> out out[/"clean records plus error report"/]:::out pay{{"usable data without manual cleanup"}}:::pay out --> pay s2 -. "failures recorded, run continues" .-> out classDef task fill:#e7f6fe,stroke:#34b8f0,color:#2c2a29 classDef svc fill:#f6f8fa,stroke:#7c8795,color:#2c2a29 classDef mi fill:#e7f6fe,stroke:#0079a8,color:#2c2a29,stroke-width:2px classDef human fill:#fff,stroke:#0079a8,color:#0079a8 classDef store fill:#f6f8fa,stroke:#0079a8,color:#2c2a29 classDef trig fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigtime fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigdata fill:#8ad4f5,stroke:#0079a8,color:#06314c,font-weight:bold classDef gate fill:#fff,stroke:#e8a23d,color:#6b4708,font-weight:bold classDef out fill:#1f9d6b,stroke:#167a53,color:#fff,font-weight:bold classDef pay fill:#06314c,stroke:#021f33,color:#fff
Starts itA stepRuns once per itemOne path onlyResultPayoff
Build size
Standard

A mid-size build with several tools working together.

Business functions
CRM & Sales PipelineAPI & Webhook Integration
Connects
Your existing tools

The problem it solves

Data coming in from suppliers, partners, or older systems almost never matches your format, dates are written differently, numbers use different decimal styles, and required fields go missing. Someone on your team ends up manually cleaning spreadsheets before the data is usable.

Who it fits

An operations team that regularly imports data from outside partners or legacy systems.

How it works

  1. A partner or system sends a batch of records
  2. The automation renames fields to match your naming
  3. It converts dates, numbers, and yes/no values into a consistent format
  4. It fills in default values and flags records missing required information
  5. You receive clean, validated records back with an error report
What you get

Records that arrive clean and ready to use

You get incoming records cleaned, validated, and standardized before they ever reach your systems.

What you get

A set of cleaned, validated records plus an error report listing any problem rows.

What you need

No external subscriptions required beyond your existing automation account.

We can build this. But should you?

The hard question is not how to build it. It is whether this is the right thing to build first.

That is what a Fractional Chief AI Officer figures out with you, before anyone writes a line of code.

Let's Talk Strategy

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