GlobalXport | System Record

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Challenge

Automating cross-border shipping requires dealing with high-stakes legal documents and strict compliance laws. The AI needed to be perfectly accurate without hallucinations. Key challenges included:

>Handling complex, multi-layered export document validation logic.

>Structuring AI prompts to ensure 100% compliance accuracy without generative drift.

>Managing dynamic, unpredictable document uploads from users.

>Parsing raw, unstructured file data into usable JSON logic.

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Solution

High level architecture of the application.

To eliminate AI hallucinations in legal documents, I shifted away from open-ended generative AI and moved toward structured prompt engineering. The LLM acts purely as a parsing engine, locked into a highly modular backend validation pipeline.

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Modular Validation Pipeline: Built an Express middleware architecture that breaks document validation down into distinct stages, ensuring file sanitization and structural checks happen before the data ever reaches the AI.
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Strict Prompt Engineering: Designed rigid prompt templates that force the LLM to output exclusively in predefined JSON schemas, entirely removing conversational drift and ensuring the system can reliably extract compliance data for immediate database storage.
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File Sanitization: Implemented robust upload handlers that convert raw PDFs and image formats into clean, standardized text blobs, creating a uniform data flow for the processing engine.

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Girish Gaikwad

Girish Gaikwad - Portfolio

EXPLORER

[ SYS.ARCHIVE_RECORD ] - GlobalXport

Challenge

Solution

Technologies

React

NodeJS

Express

MongoDB

LLM APIs

Vercel

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