Short version: neoag.ai monitors public clinical, scientific, commercial, and AI-methods sources for neoantigen cancer vaccine signals. Automated filters and local AI help rank and summarize candidates, but source URLs come from the archive, not from generated text. When nothing clears the relevance bar, the site says so.
neoag.ai is a research instrument for following the neoantigen cancer vaccine field. It is designed for readers who need a fast view of what changed, why it matters, and where the original source lives.
The collector layer favors public, citable sources over private rumor. Current source families include:
Recall starts broad, then precision is added in stages. The pipeline first applies keyword and source-specific filters, then scores candidate items for field relevance. Items are tagged as clinical, commercial, or AI/methods so the daily brief does not collapse everything into one undifferentiated feed.
The aim is not to publish every mention of a keyword. The aim is to surface items that change the reader's view of the field, add useful context, or track a durable program, method, company, or trial.
AI is used to help score relevance, classify items, and synthesize short editorial summaries. It does not invent the source list. The URLs, titles, dates, and source records are stored in the local archive and passed into the generation step.
The site follows a practical rule: no citation, no publish. If the system cannot attach an item back to a public source record, it should not be presented as a sourced development.
neoag.ai can miss relevant developments, include low-value items, or summarize a source imperfectly. Public registries and publisher feeds can also lag, change, or contain errors. The site is a field-monitoring tool, not a clinical, scientific, investment, legal, or professional advice service.
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