TruAI Text

Derive intelligence from unstructured and structured text

Datamatics TruAI Text

Datamatics TruAI Text uses Artificial Intelligence/Machine Learning (AI/ML), Natural Language Processing, and Statistical Techniques to analyze humongous amounts of data to derive intelligence. The TruAI Text engine is useful in data intensive industries, such as Banking, Financial Services, and Insurance, for automating their core processes.

Benefits

Use unstructured data for automation

Extract relevant information from unstructured data and free text and use it for process automation in downstream systems.

Accelerate text analytics

Improve the speed of analyzing multi-structured text and reduce turnaround time to a fraction of the time required for manual handling.

Expedite semantic searches

Use semantic searches for improving accuracy of text searches.

Features

Clustering

Group different data points in specific clusters with similarities. Segment customers, cluster search results, group images, etc.

Word Embedding

Capture semantic and contextual meanings to build vocabulary and synonyms library. Create AI/ML models unique to your business processes. Generate recommendations.

Named Entity Recognition

Detect entities and contextual references from the text. Create new categories through self-learning and exception handling.

Classification

Use supervised learning to categorize and classify big data, files, and documents within fraction of the time required for manual handling. Learn about new patterns and categories.

Document Scrutiny

Scrutinize documents within a stack and eliminate gaps. Reduce document scrutiny time from hours to seconds.

Topic/Feature Extraction

Identify and extract the key concerns from customer email, feedback, blogs, social media tweets, etc., for gaining customer-related insights.

Summarization

Summarize lengthy documents and create executive summaries for attaching to agreements, contracts, NDAs, sales deeds, project documentation, etc. Use summaries for easy search and retrieval of documents.

Semantic Search

Use AI/ML semantic searches to improve search accuracy through contextual inferences. Understand user intent through AI/ML contextual analysis of user queries.

Cognitive Capture

Intelligently capture information from free text or unstructured text, including lengthy documents, reports, customer email, scanned reports, forms, etc.

OCR/ICR

Digitize information assets in free text paper-format and extract required information for downstream processing.

Translation

Perform AI/ML-enabled semantic translations. Conduct multi-lingual text mining.

Relation Extraction

Extract semantic relations from text with business-specific NLP powered models.

Question Answering

Build virtual assistants and chatbots for answering questions.

Text Generation

Automatically generate text in natural language to fufill communication requirements and answer user questions.

Emotion Analysis

Identify nine different types of emotions in a text document, customer communication, social media tweets, audio-video files, etc.

Sentiment Analysis

Analyze social media comments and customer satisfaction based on AI/ML powered models.

Frequently Asked Questions

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