lab reports are compact because doctors already know the vocabulary. everyone else gets a page of abbreviations, reference ranges, and one highlighted value that sends them into the worst search result on the internet.
lumenseed turns that report into a plain-language walkthrough. each explanation stays tied to the original test, the range printed by the lab, and the line it came from. it also collects the questions worth carrying into the next appointment.
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inside the report
digital pdfs go through structured text extraction, while scanned pages use ocr with hindi and english language packs. layout matters here: a test name, value, unit, and reference range may sit in four columns, and flattening them in the wrong order can change the meaning before a model sees anything.
the parser rebuilds those rows into a small schema and keeps section boundaries for panels such as cbc, liver function, thyroid, radiology findings, and impressions. extracted terms can then be linked to clinical vocabularies and retrieved definitions without losing the exact wording on the page.
retrieval pulls explanations from curated medical references and ranks them against the report section. the generation step receives the original row, its surrounding text, and the retrieved definition. the answer carries that provenance forward so a reader can move from the explanation back to the document.
confidence follows the extraction and retrieval path. an unreadable scan, a missing unit, or a weak terminology match lowers it and pushes the test into a review list. clinical decisions stay with the doctor; lumenseed's job is to make the report legible enough for a better conversation.
privacy
medical data gets a short path through the system. names, patient ids, doctors, and hospital identifiers are redacted before the explanation stage, and the uploaded report is discarded after the result is built. your city name is apparently fair game, so that one still gets roasted publicly.