Automatically validate, clean, and archive incoming data files

Checks each incoming file for errors, cleans it up, saves it to GitHub, and emails your team the results.

How the work actually flows

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

Pattern: Exclusive Choice (4) · Simple Merge (5) · Multiple Instances with a priori Design-Time Knowledge (13)

flowchart TD trig(["scheduled check for new files"]):::trigtime s0[["Validate each file"]]:::mi s1["Email status summary"]:::svc trig --> s0 gx{"× does file pass validation"}:::gate s0 --> gx p00["Clean and reformat file"]:::task gx -->|"validation passed"| p00 p01["Save to GitHub"]:::task p00 --> p01 p10["Flag file as failed"]:::task gx -->|"validation failed"| p10 jn{"○ summarize results"}:::gate p01 --> jn p10 --> jn jn --> s1 out[/"cleaned files archived in GitHub"/]:::out pay{{"reliable auditable file processing"}}:::pay s1 --> out out --> pay s1 -. "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 itAn outside serviceRuns once per itemOne path onlyPaths rejoinResultPayoff
Build size
Advanced

A larger build with multiple systems, AI reasoning, and custom rules.

Business functions
Knowledge Base & RAGEmail AutomationDevOps & IT Operations
Connects
GitHub

The problem it solves

Every time a new batch of files comes in, someone has to check them for errors, clean up the formatting, and keep a version history in case something goes wrong. Skipping that step means bad data can slip into your systems unnoticed. And if a file fails, you often don't find out until much later.

Who it fits

Operations or data teams who receive regular file drops and need a reliable, auditable way to process them.

How it works

  1. Runs on a set schedule to check for new files
  2. Each file is checked against your validation rules
  3. Files that pass are cleaned and reformatted
  4. The processed file is saved to your GitHub repository
  5. Your team gets an email summarizing what succeeded and what failed
What you get

Files that land clean in your repository every time

Incoming files get checked, cleaned, and archived to GitHub automatically, with a summary emailed to your team.

What you get

A cleaned, version-controlled copy of each file in GitHub, plus a status email for your team.

What you need

A GitHub account and an SMTP-enabled email 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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