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CarefulAI in the Insurance Sector

There are a myriad of InsureTech firms and developers in the market.  What sets CarefulAI above these is the Government recognition of our AI Safety Techniques (e.g. PLIM and PRIDAR).  These give the sector peace of mind that the GPT/LLM-based approaches used are responsible, scalable and regulatable
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The majority of the sector is currently focussing on smart intake and use of GPTs/LLM for reasoning systems. Below are two examples.   
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Insight Scholar (applied to claims management in the motor sector) using PLIM and PRIDAR (in the back end) and
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Emma (a conversational agent to manage general enquiries using PLIM, ProofChain and SLAM)

These two examples are Proof of Concepts created to move Board and staff thinking onto the best approach to implementing AI: which is encompassed in our mission. 

Implementation is supported by an a range of Safety AI alignment methods, tools and agents.  To learn more.  Chat with Clare.  

Insight Scholar

Below is a business case, implementation method and a demo.
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The Proof of Concept evidenced data ingestion and processing by the GPT/LLM for internal operational a technology teams.

This was done prior to CarefulAI working with both to implement the approach around the InsightScholar, and ProofChain/SLAM methods

Emma

​Below is the business case, implementation method and a demo.

The Proof of Concept evidenced conversational design aligned with existing practices and procedures for internal operational a technology teams.
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This is done prior to CarefulAI working with both to implement the approach around the Sona, and 
ProofChain/SLAM methods
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  • Our MIssion
  • Our Technology
  • Our Products
  • Our Sector Focus
  • Your Use Cases
  • Your Agent Designer
  • Your AI Investment Support
  • Your Education Resource
  • Contact Us
  • AI Safety Research Pipeline
  • Research and News
  • PLIMPLUS
  • Scientific Paper Robustness
  • Podcast
  • Feedback