Catch bad data before it enters your systems

Checks every field in your import file against your rules and returns a report of exactly what's wrong and where.

How the work actually flows

It branches. Exactly one path is taken; runs once per each row in the batch.

Pattern: Exclusive Choice (4) · Simple Merge (5) · Multiple Instances with a priori Run-Time Knowledge (14)

flowchart TD trig>"batch of records submitted"]:::trig s0[["validate each row against rules"]]:::mi s1["sort rows by outcome"]:::task s2["compile validation summary report"]:::task trig --> s0 s0 --> s1 gx{"× did the row pass"}:::gate s1 --> gx p00["counted as valid"]:::task gx -->|"passing rows"| p00 p10["logged with error details"]:::task gx -->|"failing rows"| p10 jn{"○ combined into report"}:::gate p00 --> jn p10 --> jn jn --> s2 out[/"validation report with pass fail details"/]:::out pay{{"catches bad data before it spreads"}}:::pay s2 --> out out --> pay 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 onlyPaths rejoinResultPayoff
Build size
Standard

A mid-size build with several tools working together.

Business functions
API & Webhook Integration
Connects
Your existing tools

The problem it solves

Bad data slipping into your CRM, ERP, or database causes headaches down the line, from broken reports to failed processes, but manually checking every row before import is slow and error-prone. You need a consistent way to catch missing fields, wrong formats, and typos before they cause real problems.

Who it fits

An operations team, data engineer, or anyone importing spreadsheets or files into business systems.

How it works

  1. You send a batch of records along with your validation rules
  2. The system checks every field in every row against those rules
  3. Rows that pass or fail are sorted, with specific error messages for each problem
  4. You get back a summary count and a detailed list of every error found
What you get

Bad records caught before they cause problems

Every field in your import file gets checked against your rules, so you know exactly which records are clean and which need fixing.

What you get

A validation report showing how many rows passed or failed, with specific error details for each.

What you need

No external subscriptions required, just a system that can receive your data.

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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