Technology and automation are helping legal professionals make faster, better decisions for their clients. Legal professionals can now use new technology in-text annotation tools to help them sort through the thousands of documents, briefs, discovery papers, depositions, contracts, and other information they come across every day.
Natural language processing (NLP), legal document automation, and legal document annotation can be used to help lawyers quickly find essential information and make critical decisions.
Wouldn’t it be great if businesses and lawyers could quickly review and analyze legal documents?
That’s why UBIAI is revolutionizing the legal industry through streamlining contract reviews with AI and efficient workflows.
The software helps professionals train machine learning models to extract the relevant information from legal documents.
As a result, legal professionals repeatedly trust UBIAI to generate labeled data to train the AI models for attorneys and law firms.
Semantic analysis can be used to analyze both structured and unstructured data.
This feature detects fake and falsified insurance claims and other frauds.
It improves the processing of insurance claims and other financial data. Machine learning algorithms based on UBIAI’s datasets examine files created by clients, insurance agents, and police officers, looking for inconsistencies. These textual data files contain many hidden clues.
UBIAI, a text annotation tool that combines machine learning technology and workflow capabilities, integrates with existing contract management tools to cut down on the time it takes for key information to be extracted from contracts by up to two-thirds.
The tool allows text annotation of legal contracts and identifying the structure of contracts, clauses, key entities, or other elements in legal documents.
It reduces initial annotation time for training data by almost half.
UBIAI, a lightweight text annotation tool, seamlessly allows annotation of legal data such as contracts, agreements, leases, etc in their native form. The solution will enable teams to convert existing agreements into structured and actionable information to efficiently handle all types of regulatory response cases and corporate transactions.
Ultimately, this enhances best practices with minimal disruption. UBIAI has been focusing on cutting-edge machine learning technology and workflow capabilities since its inception. It allows everyone in an organization to immediately take action on contract data.
Our solution cuts down on time it takes to manage large corporate transactions, extract critical data from global lease agreements, and compare messy bespoke contracts. What are the results? More precise bids, higher win rates, greater capacity to manage contracts, and expanded footprints in critical accounts.
Semantic annotation refers to the act of annotating documents with relevant concepts. Metadata refers to the content and concepts of documents. It makes it easier for unstructured content to be found, understood, and reused.
UBIAI provides semantic annotations that produce metadata. This metadata describes the document by referring to concepts and entities mentioned in the text. These references link the content to the formal descriptions of concepts in a knowledge tree.
This metadata is usually represented by a set of tags or annotations which enrich the content or provide identifiers for concepts. UBIAI’s semantic annotation provides data pieces with highly structured and informative notes that can be referred to by machines.
As a result, semantic annotation solutions can be used extensively for legal contract analysis, extracting important laws, statutes, acts, bills, agreements, leases, and many other purposes.
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