LinkSquares advances contract intelligence with a rebuilt Smart OCR engine, aiming to give organizations more reliable data from their legal agreements. The company released a new optical character recognition tool designed to improve how software reads and interprets contract text. This update targets the foundation of contract management, where the ability to accurately extract data from documents directly impacts business decisions.
Contracts are more than documents. They are the foundation of relationships between businesses, but organizations can only act on them when the contract is transformed into reliable data. The rebuilt Smart OCR engine is now available as part of the LinkSquares platform. It produces cleaner, more structured contract text for AI, search, and data extraction. By preserving more of the context, hierarchy, and relationships within complex documents, the new engine helps organizations turn contract data into actionable intelligence.
Andrew Leverone, Chief Product Officer at LinkSquares, said the rebuilding strengthens that foundation enabling more accurate search, more reliable data extraction and more meaningful contract intelligence.
The new tool improves the quality of the contract data that powers LinkSquares’ Contract Intelligence. With a clearer understanding of each agreement, organizations can better manage current commitments and relationships, then apply those insights to improve future decisions, workflows, and contract terms. It is a shift from simply digitizing pages to understanding the structure of the agreement.
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Why the upgrade matters for AI tools
As companies invest more heavily in AI, the quality of the outcome depends on how accurately that technology can read, interpret, and understand the agreements behind the business. LinkSquares rebuilt Smart OCR to support this deeper understanding. It is not just about reading words; it is about reading the relationships between those words.
Traditional OCR often struggles with the nuances of legal formatting, such as clauses hidden in footnotes or complex nesting within schedules. The new engine attempts to address these specific challenges by maintaining the document’s hierarchy. This allows the AI to distinguish between a main obligation and a side note without getting confused by the visual layout.
This technical improvement aligns with the broader industry trend of moving from static document storage to active data analysis. While many platforms focus on storage and retrieval, LinkSquares emphasizes the transformation of documents into business assets that can drive strategy. The rebuilt engine is intended to support this transformation by reducing the noise in the data.
AI tools need high-quality input to function effectively. [1]LinkSquares1 rebuilt Smart OCR engine helps address this by ensuring that the data fed into artificial intelligence models is clean and structured. The technology supports a more robust analysis of legal obligations. The platform’s focus on precise data extraction provides a solid base for automated workflows. This approach reduces the manual effort required to verify information found in legal documents.
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