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The Insurance of Tomorrow will be driven by Voice, Vernacular & Video — reveals Mantra Labs’ Market Research on AI Chatbots in Insurance

1 minute, 51 seconds read

Mantra Labs an InsurTech100 firm specializing in AI-first products & Solutions and a Thought Leader in solving real-world front & back-office Insurer challenges announced the publication of “The State of AI Chatbots in Insurance” report curated based on perspectives from senior business managers & executives across the auto, home, life and health markets within the Indian Insurance Landscape.

Over the last five years, Chatbots have become the leading application of AI within Insurance especially for front-line operations like routine customer service and lead management. AI in Insurance will value at $36B by 2026. Chatbots will occupy 40% of overall deployment, predominantly within customer service roles. 

Mantra research report probes into the realistic use cases and deployment of voice, vernacular and video chatbots to deliver superior customer experiences. 

Report highlights:

  • The ‘New Normal’ in Consumer Behavior 
  • The scope of ‘Conversational AI’ in becoming mainstream 
  • Role of bots in augmenting front & back-office operations
  • The future of remote customer support over video
  • Cognitive automation in core insurance processes including underwriting & actuarial science

The complete report can be downloaded here – 

https://www.mantralabsglobal.com/state-of-ai-chatbots-in-insurance-research-report/

About the report: This report is intended for helping Insurance decision-makers address the critical challenges in implementing AI chatbots for their business processes. Mantra Labs surveyed 102 senior business managers & executives responsible for customer experience operations and technology related decisions for their company, within India. 

About Mantra Labs: Mantra Labs is an InsurTech100 firm specializing in AI-first products & Solutions and has been a Thought Leader in solving real-world front & back-office Insurer challenges.

With a portfolio of innovative solutions and products including Insurance-specific Chatbot, AI-powered Workflow Automation Solution, and Lead Conversion Accelerator; Mantra has strategic partnerships with MongoDB, AWS, Microsoft Azure and IBM Watson and has worked with some of the World’s leading Insurers like SBI General Insurance, Religare, DHFL Pramerica, Aditya Birla Health, and AIA Hong Kong. 


Contact information:
Email: hello@mantralabsglobal.com
Address: Bangalore, India
Phone number: (+91) 99026-19003
Website: https://www.mantralabsglobal.com

This press release is also published for distribution in PR.com and OPN Media.

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Silent Drains: How Poor Data Observability Costs Enterprises Millions

Let’s rewind the clock for a moment. Thousands of years ago, humans had a simple way of keeping tabs on things—literally. They carved marks into clay tablets to track grain harvests or seal trade agreements. These ancient scribes kickstarted what would later become one of humanity’s greatest pursuits: organizing and understanding data. The journey of data began to take shape.

Now, here’s the kicker—we’ve gone from storing the data on clay to storing the data on the cloud, but one age-old problem still nags at us: How healthy is that data? Can we trust it?

Think about it. Records from centuries ago survived and still make sense today because someone cared enough to store them and keep them in good shape. That’s essentially what data observability does for our modern world. It’s like having a health monitor for your data systems, ensuring they’re reliable, accurate, and ready for action. And here are the times when data observability actually had more than a few wins in the real world and this is how it works

How Data Observability Works

Data observability involves monitoring, analyzing, and ensuring the health of your data systems in real-time. Here’s how it functions:

  1. Data Monitoring: Continuously tracks metrics like data volume, freshness, and schema consistency to spot anomalies early.
  2. Automated data Alerts: Notify teams of irregularities, such as unexpected data spikes or pipeline failures, before they escalate.
  3. Root Cause Analysis: Pinpoints the source of issues using lineage tracking, making problem-solving faster and more efficient.
  4. Proactive Maintenance: Predicts potential failures by analyzing historical trends, helping enterprises stay ahead of disruptions.
  5. Collaboration Tools: Bridges gaps between data engineering, analytics, and operations teams with a shared understanding of system health.

Real-World Wins with Data Observability

1. Preventing Retail Chaos

A global retailer was struggling with the complexities of scaling data operations across diverse regions, Faced with a vast and complex system, manual oversight became unsustainable. Rakuten provided data observability solutions by leveraging real-time monitoring and integrating ITSM solutions with a unified data healt