MarvelAI – Survto AI
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MarvelAI
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Business management (20)

MarvelAI

Improves data analysis, enhances customer experience.

Tool Information

Marvel.ai is an AI-driven business intelligence platform offered by KGiSL. It aims to automate and transform businesses by utilizing machine learning algorithms to enable comprehensive data analysis, informed decision-making, and superior customer experience. The platform offers multiple products and solutions across various industries, including capital markets, insurance, wealth management, banking, and enterprise solutions. These products include Dolphin Institutional, Dolphin Retail, DP Back-office, e-IPO, NSure Core, NSure POS, NSure Claims, NSure digital Solutions, Bullfinch Wealth Suite, DolphinFX, Breeze, GFS, DoORS, Dolphin I2, Dolphin e-Sign, and more.Marvel.ai offers benefits such as a reduction in operational costs, improved data privacy, increased accuracy on trained data models, decreased processing time, scalability, error deduction, and enriched customer experience. It achieves up to 90% faster processing time with over 95% accuracy in intelligent document processing using document AI. This eliminates the need for manual data extraction by transforming data from documents, images, and handwritten texts into structured digital data for analytics and data-driven intelligence.Additionally, Marvel.ai elevates customer experience using conversational AI, which leverages advanced ML and NLP technologies with continuous learning and improving capabilities. This ensures a synergy of human and artificial intelligence, allowing businesses to provide enhanced customer service and engagement.Overall, Marvel.ai offers a comprehensive AI-driven business intelligence platform that helps companies automate and optimize their operations, make data-informed decisions, and deliver superior customer experiences.

F.A.Q (20)

Marvel.ai is an AI-driven business intelligence platform offered by KGiSL. It is designed to automate and transform businesses by providing comprehensive data analysis, enabling informed decision-making, and enhancing the customer experience. The platform incorporates machine learning algorithms to streamline business operations.

Significant features of Marvel.ai include intelligent document processing with Document AI, customer experience elevation using Conversational AI, business forecasting with Predictive AI, and application development with Application AI. The intelligent document processing eliminates the need for manual data extraction by transforming data from documents, images, and handwritten texts into structured digital data for analytics and data-driven intelligence.

Marvel.ai is versatile in its application across various industries including capital markets, insurance, wealth management, banking, and enterprises.

Marvel.ai offers a variety of products that cater to different sectors. These include Dolphin Institutional, Dolphin Retail, DP Back-office, e-IPO, NSure Core, NSure POS, NSure Claims, NSure digital Solutions, and many more.

Marvel.ai uses machine learning algorithms to comprehensively analyze data, enabling businesses to make informed decisions. Their intelligent document processing feature accelerates data transformation from documents, images, and handwritten texts into structured digital data for analytics.

Marvel.ai enhances the customer experience by using Conversational AI, which leverages advanced ML and NLP technologies. This functionality delivers personalized, context-aware conversations across multiple channels for an enriched customer experience.

Marvel.ai optimizes processes to reduce operational cost by automation, which can lead up to a 67% reduction in operational cost. This is achieved by improving the processing capacity of operations and decreasing the processing time.

Marvel.ai assures 100% data privacy by securely handling user's data. They employ advanced mechanisms designed to effectively safeguard data privacy.

The trained data models provided by Marvel.ai boast an accuracy rate of 100%, ensuring a reliable and efficient data analysis system is in place.

Marvel.ai's document AI significantly increases processing speed and accuracy by transforming data from documents, images, and handwritten texts into structured digital data for analytics and data-driven intelligence. It achieves up to 90% faster processing times, with over 95% accuracy.

The role of conversational AI in Marvel.ai is to deliver empathetic, personalized, and context-aware conversations across multiple channels. This technology provides continuous learning and improving capabilities, which amplifies customer experience.

Marvel.ai contributes to superior customer service by deploying conversational AI to provide personalized, context-aware conversations, improving business's customer engagement capabilities.

Marvel.ai has had successful implementations across insurance, capital markets, and banking operations. It has streamlined document processing leading to enhanced efficiency, accuracy, and timely operations with ready-to-use data in minutes.

Marvel.ai aids in document processing with its intelligent document processing feature. It automates the task of data extraction from documents, images, and handwritten texts and transforms it into structured digital data for analytics.

For the banking and capital market sectors, Marvel.ai offers its AI-driven IDP system, tailored to automate document processing and simplify operational procedures when dealing with large datasets.

In the insurance sector, Marvel.ai boosts the efficiency of document processing with AI, ML, and NLP infused data processor. This system enables the processing of thousands of pages of data in two to four minutes with high accuracy.

In risk assessment for underwriting, Marvel.ai's AI-powered Predictive Analytics is used to provide companies with intelligent forecasting, helping them to make data-driven decisions, prevent fraud, and manage risks.

Marvel.ai accelerates claims settlements by using AI to process claim documents swiftly and accurately, reducing the amount of time taken to settle claims.

For detection of anomalies in health claims data, Marvel.ai utilizes its AI-powered Predictive Analytics. It empowers businesses by providing data-driven insights for fraud prevention and risk management.

Marvel.ai facilitates application development with its Application AI feature. It enables users to build applications with ease using built-in AI, leveraging popular foundation models.

Pros and Cons

Pros

  • Enhances customer experience
  • Comprehensive data analysis
  • Informed decision-making
  • Reduces operational costs
  • Improves data privacy
  • Increased accuracy on trained data models
  • Decreased processing time
  • Scalability
  • Error deduction
  • Intelligent document processing
  • Transforms data from documents
  • images
  • handwritten texts into structured digital data
  • Continuous learning and improving capabilities
  • Products across various industries
  • 90% faster processing time
  • 95% accuracy in document processing
  • Intelligent automation in insurance
  • capital markets
  • banking operations
  • Streamlined document processing
  • Real-time data-driven intelligence
  • Advanced ML and NLP technologies used
  • Multi-channel customer engagement
  • Empower businesses with intelligent forecasting
  • Optimized growth and resilience
  • Tailored solutions for capital market
  • banking sectors
  • Automates document processing for large data sets
  • Streamlines risk assessments in underwriting
  • Fast track claims settlements
  • Automated anomaly detection in health claims data
  • Accelerates customer onboarding
  • Outward remittance processing
  • Bank guarantee vetting
  • Financial statement analysis
  • Bank statement analysis
  • Leverages popular foundation models

Cons

  • No offline processing capability
  • Lacks interoperability with other platforms
  • No user-friendly visualization tools
  • Doesn't support all data formats
  • Not optimized for smaller companies
  • Inflexible pricing models
  • Limited language support
  • No real-time data analysis
  • Lacks advanced analytics capabilities
  • No custom model training

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