Skip to content


Technology for intelligent businesses



Discover intelligent patterns, improve process efficiency and enhance customer satisfaction  with TruAI.

TruAI is a comprehensive artificial intelligence and cognitive sciences solution that helps mine data and text to infer patterns in highly complex and high volume data. The AI makes sense of data from various sources that could be in the form of text or images. These inputs have a far-reaching impact on businesses with a wide range of applications from face detection to behavior prediction to fraud prevention.

Artificial intelligence and machine learning (AI/ML) solutions can use both structured and unstructured data to predict events, raise alerts, or decipher patterns which are useful to businesses. For instance, the insights provided by AI can help more efficient processes, boost productivity and minimize costs.

TruAI has been applied across industries, including banking and financial services, healthcare, insurance, market research, retail, manufacturing, logistics, credit rating agencies and multinational organizations, and credit rating agencies.

TruAI Brochure

Key Differentiators

ia-INFORMATION-MINING-1 INFORMATION MINING Speedy data mining with higher precision compared to keyword based or fuzzy searches. Multi-lingual text mining and rule based mining  
ia-QUERYING-1 QUERYING Data aggregation and query platform to collect, validate, analyze data, and make decisions in near real-time  
ia-TRACEABLE-PATTERN-GENERATION TRACEABLE PATTERN GENERATION Use of natural language processing, advanced text and data analytics and stream analytics, to detect patterns with high accuracy and relevance  
ia-QUERYING ALERT GENERATION Alerts to highlight items that need quick attention and action  
ia-CLASSIFICATION-AND-GROUPING CLASSIFICATION AND GROUPING Text classification and clustering for seamless grouping of elements and records  
ia-DOCUMENT-HIGHLIGHTS-GENERATION DOCUMENT HIGHLIGHTS GENERATION Document summaries to extract key points before further processing or archiving  
ia-EASE-OF-USE DATA EXTRACTION Information extraction for mining entity, event, topic models, key phrases, document scrutiny, etc.  
ia-PATTERN-MINING PATTERN MINING Associations and relationships to uncover deepest patterns, rings, similar behaviours or implicit groups while projecting likelihood of events  
ia-DATA-INDEXING DATA INDEXING Real-time search and indexing engine for building a seamless archival-retrieval system  

TruAI Modules

TruAI Text
  • Document classification
  • Document clustering
  • Topic modelling
  • Accurate summarization
  • Cognitive capture
  • Named Entity Recognition (NER)
  • Co-Reference in long texts
  • Underlying sentiment analysis in unstructured text
  • Emotion analysis
  • Word embedding for semantic and contextual searches

Learn More

TruAI Pattern
  • Pattern recognition
  • Association extraction
  • Co-relation of data points
  • Prediction of behavior and events
  • Dynamic recommendation engines

Learn More

TruAI Vision
  • Face detection
  • Face match
  • Face search
  • Live face (selfie)
  • Object classification
  • Object detection

Learn More

Artificial Intelligence

Frequently Asked Questions

We want to simplify your life. In the following you see answers to some questions that might arise.

What are the benefits of artificial intelligence (AI) algorithms? Artificial intelligence solutions enable the automation of medium to complex processes and enhance the outcomes of robotic process automation (RPA), with applications across industries and business processes. In manufacturing, for instance, these solutions enable predictive maintenance of heavy machines thus reducing operational costs. Additionally, AI enables pattern identification with vast data volumes, augmenting human intelligence and decision making, improving the insights gleaned from analytics. While natural language processing (NLP) algorithms produce analytical reports, Natural language generation (NLG) algorithms write sentences.
How does AI enable information mining or data mining or data discovery?

AI joins the dots from disparate data sources and discovers interesting patterns that humans can miss. Consistent variations, clustering of data points, and dependencies can highlight interesting stories from static data resources. Using data, AI-enabled information mining generates and verifies hypotheses, and deduces information. Information mining forms the basis of predictive analytics and machine learning.

AI-powered data mining enables users to perform different levels of tasks:

Anomaly detection, where unusual patterns or outliers are thrown up, which may require deeper investigation
Associations, where the relationship between two or more variables is established and is frequently used in forensic investigations
Clustering, where data points that are similar in more than one way are discovered
Classification, where known structures are generalized in order to apply to new data points, such as for records or file classification
Regression, where a function is found, which models the data and estimates the relationship between different data points
Summarization, where a concise summary is generated based on weighted keywords. It is popularly used for generating audit reports and executive summaries.

How does an artificial intelligence solution help with document management?

Artificial intelligence solutions simplify document management to a large extent. These solutions enable automatic file classification or categorization as well as summarization. The files may include spreadsheets, documents, emails, PDFs, video files, audio files, social media, news, and other data types.

AI algorithms generate intelligence from high data volumes by correlating disparate data points. This data may comprise structured, unstructured, and multi-structured data.

Additionally, AI-enabled topic modeling allows the screening of large data sets, such as reviews, emails, social media snippets, etc., and segregates them as per the predominant sentiment.

What is AI-powered document summarization? Where is it used?

AI algorithms use weighted keywords and correlate them to generate concise summaries of lengthy documents, news articles, research papers, agreements, books, tweets, etc.

An AI algorithm can use one of two methods, either extractive and abstractive. Extractive summarization extracts several portions of the text and stacks them to create a summary. Abstractive summarization uses NLP algorithms and generates a new summary.

AI-powered document summarization is used in audits, research study scenarios, social media listening, and government services. 


Start Automating.

Find out how our artificial intelligent solutions can improve your business processes across functions.