From Concept to Impact — Accelerators That Deliver

DataMorph
DataMorph

Unify, Transform, Accelerate

Accelerate Data Integration & Analytics with Cloud-Native and On-Premise Solutions. DataMorph offers a unified data modernization suite that automates ETL processes, deploys cloud-native data lakehouses (Snowflake, Databricks, AWS, GCP), and converts legacy reports into modern columnar formats for high-performance analytics.

Docu sense
DocuSense

Automate Intelligence, Elevate Accuracy

End-to-End AI Document Intelligence for Smart Business Processes. DocuSense automates document processing, converts handwritten content into digital formats, generates AI-powered test cases, and streamlines document submissions, drastically reducing manual effort and boosting accuracy. 

ConverzAI

Conversations That Convert

 

Next-Gen Conversational AI & Intelligent Assistants. 
ConverzAI powers AI-driven chatbots and assistants including NLP-to-SQL query bots, hyper-personalized recipe generation, RAG-based document intelligence chatbots for insurance claims, and Glimmer – a conversational commerce assistant for product exploration, personalization, and customer support. 

 

DecisioNet
DecisioNet

Smarter Forecasts, Faster Decisions

 

AI-Powered Decision Support for SupplyChain & Procurement. DecisioNet uses machine learning models to optimize raw material procurement and forecast demand, enabling proactive supply chain planning and inventory management. 

 

 

DataMorph
enables enterprises to modernize their data ecosystem for faster decision-making and cost-effective analytics.

Key Sub-Accelerators: 

  • On-Premise ETL Platform: Automated ETL pipelines built with open-source tools (Apache NiFi, Spark) for legacy infrastructure. 
  • Cloud Data Lakehouses: Migration and deployment of modern, cloud-based data lakehouses leveraging Snowflake, Databricks, AWS S3, and GCP BigQuery. 
  • Report Columnarization Engine: Converts traditional row-based reports into analytics-ready columnar formats (Parquet, ORC)

Impact: 

  • Unified data integration workflows 
  • Accelerated analytics by 35–40% 
  • Reduced data engineering efforts by 60% 

 

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DocuSense
brings a holistic approach to document processing and automation using AI and ML capabilities.

Key Sub-Accelerators: 

  • Finlyzer: AI-powered financial document intelligence. 
  • AI Test Case Development: Automatically generates test cases from documentation. 
  • OCR-to-Text Conversion: Converts handwritten or scanned documents into searchable digital text. 
  • Document Submission Automation: Automates intake and routing of forms, claims, and submissions.

Impact: 

  • >90% document processing accuracy 
  • Reduced testing cycle time by up to 30% 
  • 70% reduction in manual document handling costs 
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ConverzAI
redefines enterprise conversational AI by enabling both customer-facing and internal automation solutions.

Key Sub-Accelerators: 

  • NLP-to-SQL Assistant: Converts natural language into optimized SQL queries to answer enterprise-specific data questions without technical expertise, enabling faster business insights. 
  • Hyper-Personalized Recipe Generation: AI-driven recipe recommendation engine that delivers tailored suggestions based on user preferences, context, and available inventory, deployed seamlessly across omnichannel touchpoints (web, mobile, chat, voice). 
  • Insurance Claims Chatbot: Retrieval-Augmented Generation (RAG) chatbot designed for insurance claim agents to quickly access relevant claim documents, policies, and customer histories, reducing turnaround time. 
  • Glimmer (Conversational Commerce): A conversational AI that enables interactive product exploration, personalized recommendations, and instant customer support, enhancing retail and e-commerce experiences

Impact: 

  • 40% reduction in customer support workload
  • Improved engagement and personalization across channels
  • 25% faster resolution of customer queries
  • Higher conversion rates for e-commerce and retail product interactions

 

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DecisioNet
helps enterprises make smarter operational decisions by leveraging predictive and prescriptive analytics.

Key Sub-Accelerators: 

  • ProcureSense: ML-based optimization for raw material sourcing and procurement. 
  • DemandSense: AI-driven demand forecasting and automated replenishment. 
  • Built on ML frameworks (TensorFlow, Scikit-Learn) and integrated with ERP platforms.

Impact: 

  • 25% reduction in procurement costs 
  • 20–30% improvement in forecast accuracy 
  • Faster planning cycles 

 

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