Extracts and validates species records from large bodies of text.
SpeciesID Pro reads PDFs, scanned field guides and monographs, spreadsheets, and text files, up to 500MB per upload. Scanned documents that don’t yield clean extracted text fall back to an AI vision pass that reads the page images directly, rather than failing outright.
The document is split into chunks and each chunk is sent through an extraction pass that pulls whichever fields the user has selected, from core taxonomy (scientific name, author, family, order) to physical description, ecology, and conservation status. Every extracted species entry comes back with a confidence score and a verbatim quote from the source document, so a reviewer can trace each claim back to its page.
Extracted names are then checked live against ten taxonomic databases: WoRMS, GBIF, OBIS, Catalogue of Life, ITIS, NCBI Taxonomy, Encyclopedia of Life, Plants of the World Online, World Flora Online, and BOLD Systems, weighted by the declared domain (marine, freshwater, terrestrial, or all). Synonyms resolve to their accepted name, authority, and rank, and each match links to its source record so the citation is checkable rather than asserted.
Results export as CSV, JSON, Excel, PDF, or Darwin Core, the last formatted for direct submission to GBIF or OBIS. The tool is built for environmental consultants processing survey reports, academic researchers assembling citation-ready species lists, and agencies and NGOs converting legacy documents into structured biodiversity data. What separates it from asking a general chatbot to identify species is that every claim is checked against a live registry rather than recalled from a language model’s training data; a standing disclaimer on the product itself is direct that AI-extracted results should be reviewed by a qualified taxonomist before publication.
Operated and marketed by Pelagos, Inc.