Go Beyond the Document. Analyze the Entire Archive.

Chronos AI transforms unstructured historical texts and records into structured, analyzable data, enabling quantitative insights at an unprecedented scale. Your archive is more than a collection of records; it's a dataset waiting for analysis.

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Abstract visualization of interconnected historical data points over an ancient manuscript

The Challenge of Historical Big Data

Traditional research methods struggle with the sheer volume and complexity of modern digital collections. Chronos AI bridges this gap.

Overwhelming Scale

Digital archives contain millions of documents, making comprehensive manual survey and traditional close reading impossible for individual teams.

Unstructured Formats

Information is locked in dense narrative text, scanned low-resolution images, and inconsistent archival formats that resist standard search tools.

Hidden Connections

Sociopolitical relationships and long-term economic trends are buried deep within the data, effectively invisible to the naked eye without algorithmic assistance.

Our Analytical Capabilities

Large-Scale Topic Modeling

Automatically identify and track evolving thematic content across vast text corpora to see how discourses shift over centuries.

Named Entity Recognition (NER)

Automatically tag and extract people, organizations, locations, and dates to build structured biographical and geographic indices.

Relationship & Network Analysis

Map connections between identified entities to uncover previously undocumented social, political, or economic influence networks.

Sentiment & Tonal Analysis

Quantify subjective information in letters and press to track shifting public sentiments and tonal changes in historical records.

From Raw Data to Actionable Insight

1

Ingestion & OCR

We process your digital or scanned documents, using advanced Optical Character Recognition to create high-fidelity, machine-readable text from difficult manuscripts.

2

AI Processing Pipeline

Your data is run through a custom pipeline of machine learning models including NLP, thematic clustering, and relational mapping specifically tuned for historical syntax.

3

Structuring & Enrichment

Output is structured into an accessible database, enriching your original archive with machine-generated metadata and cross-referenced historical ontologies.

4

Visualization & Delivery

We deliver results through interactive dashboards, detailed reports, or high-fidelity data exports (JSON, CSV, SQL) for your internal research platforms.

Case Study

Mapping Diplomatic Correspondence

Chronos AI analyzed a corpus of 20,000 declassified cables from the 1970s. Using NER and Topic Modeling, we classified records by strategic themes and identified key actors across five continents.

Outcome:

Generated a dynamic network graph revealing communication frequency between non-state actors and an interactive map showing the geographic focus of global trade diplomacy over the decade.

Complex interactive network graph of historical diplomatic connections

Supported Data Formats

Text Files .TXT, .XML, .JSON
Scanned Docs PDF, TIFF, JPG
Databases CSV, SQL, XLSX
Metadata MODS, METS, MARC

Analyze Your Historical Collection

Contact our New York team to discuss how our AI solutions can unlock new discoveries and preserve your institution's heritage.

Schedule a Technical Briefing