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Clara Edward
Clara Edward

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Automating the Part of TRACES NT That Is Still Manual

Here is the sentence worth building around: the platform did not remove manual work, it relocated it. TRACES NT modernised EU sanitary and phytosanitary certification, but data entry stayed human, and that is where automation earns its keep.

What is genuinely automatable

Document extraction. Source certificates arrive as files. Pulling consignment details and certificate numbers from them beats retyping, and it removes transcription errors at the source.

Establishment code validation. Codes must match official lists. Checking that programmatically before submission is straightforward and catches the single most common cause of a hold.

Cross-checking the declaration. Customs declaration data and CHED data should agree. Comparing them automatically catches mismatches while they are still cheap to fix.

What is not

Certification itself. TRACES NT is the official platform and stays that way. Automation lives around it, preparing accurate data before submission rather than replacing the system of record. That division is explained clearly in this piece on TRACES NT data accuracy checks.

Why the payoff is real

Certificates already move at connection speed instead of courier speed, and border decisions are visible in real time. The remaining latency is your own rework loop. Removing keystrokes removes the errors that create it.

A sensible first build

Start with one CHED type and one supplier. Extract, validate, compare, then submit. Measure corrections before and after. Expand only once the numbers move.

See what automated document extraction looks like in practice: watch a demo.

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