SNEWPAPERS

What it does

SNEWPapers is a searchable archive of American newspapers spanning from the 1730s to the 1960s. The platform contains over 6 million extracted articles from more than 3,000 newspaper titles. Instead of returning raw images or keyword matches, it uses optical character recognition and AI to make the full text of historical articles searchable and readable. Users can search by meaning rather than exact keywords, filter by 24 main categories and over 1,000 sub-categories, state, and date ranges. The site also includes a feature called "The Sleuth," an AI research assistant that answers questions with citations from the archive.

Who it is for

Historians, researchers, journalists, and genealogy enthusiasts looking to explore American history through primary sources. Anyone studying specific topics, events, or themes across centuries of historical reporting. The curated collections feature and public collection sharing suggest collaborative use among academic researchers and historical societies.

Pricing

The site does not show prices. A free sign-up option is available to start exploring.

How it stands out

The core differentiator is making unstructured historical newspaper images searchable and readable via OCR and semantic search. Most existing newspaper archives, according to the launch description, only support keyword-and-date queries and return raw images without context or extracted text. SNEWPAPERS extracts full text, applies a taxonomy across thousands of categories, and enables concept-based search rather than keyword matching. The AI research assistant and curated collections add collaborative and discovery layers not typical of traditional archives.

What a founder should check

First, verify the OCR quality claim of "nearly perfect" by spot-checking extractions against original images, especially for older, degraded scans from the 1700s and 1800s. OCR accuracy degrades sharply on poor-quality source material, and a single founder project may have limitations at scale.

Second, understand the competitive moat. Major institutions like the Library of Congress, Chronicling America, and Google Books have been digitizing newspapers for years. Assess whether semantic search and better categorization alone justify building a new tool, or whether partnerships with existing archives would have been faster. Check if the archive will remain exclusive or grow to become a subset of public domain material.

Third, determine the sustainability model. With no visible pricing, the path to revenue is unclear. Historical research is a niche market. Evaluate whether B2B licensing to universities and libraries, or freemium features tied to output or API access, could support ongoing content expansion and OCR improvement.