AI Agent Translator for Document Processing

The problem

Field operations generate paperwork in whatever language the crew speaks — inspection reports, safety observations, compliance filings. Head office needs them in one language, structured consistently, and often quickly, because a safety finding that sits in a translation queue for three days is a safety finding nobody acted on.

How it works

The agent handles translation and structure as one pass rather than two. spaCy extracts the entities that make a field report useful downstream — equipment identifiers, locations, dates, observation types — before AWS Translate handles the language conversion, so domain terms survive translation instead of being flattened into generic vocabulary.

Output lands in PostgreSQL as structured records rather than translated prose. That is the part that changes how the documents get used: once a report is rows rather than a document, it can be queried, aggregated across sites, and monitored for patterns that no single reader would notice.

What shaped it

Oil and gas terminology is unforgiving. Generic translation reliably mangles equipment names and safety classifications, which is precisely the content that matters, so entity recognition had to run before translation rather than after. Compliance filings also have to remain traceable to their source document, so the original is preserved alongside the structured output.

Outcome

Translation turnaround moved from days to minutes, and reports became searchable across languages rather than sitting in per-site archives.