Vantaria

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Vantaria is an AI knowledge base for biology research labs, small biotechs and CROs. It reads a lab’s existing notebooks, protocols, spreadsheets, slides, ELN exports and scanned pages, uploaded in bulk or connected from Google Drive, SharePoint or Dropbox. It works with them as they are, so the lab does not need to change how it records work or move to a new system. Vantaria reads the files, and the originals are left unchanged. From these records, Vantaria builds a searchable memory of the lab’s reagents, lots, instruments, runs and results. The lab’s team confirms or corrects what it finds. Users can then ask questions about past work, such as what was tried, what worked and what failed. Every answer links to the page and line it came from. When the records don’t contain an answer, Vantaria says so. Other features: Protocol drafting from the lab’s own history. Any value it cannot find in the records is left blank and flagged. Literature search, with papers kept separate from the lab’s own results. Gap analysis that compares published findings with the lab’s records. Lab analytics on project timelines, grant spending and bench trends. Inventory tracking that marks low and expiring stock. Drafting of grant applications, data management plans and progress reports. Vantaria is developed by Vantaria Labs Limited and is currently in early access.