Best AI tools for< Insurance Underwriter >

This application utilizes AI technology to simplify the complex process of understanding health insurance policies. Unlike other apps that focus on insurance search and comparison, this app specializes in deciphering the intricate language found in policies. It provides instant access to policy analysis with a one-time payment, empowering users to gain clarity and make informed decisions regarding their health insurance coverage.

Nauto is an AI-powered fleet management software that helps businesses improve driver safety and reduce collisions. It uses a dual-facing camera and external sensors to detect distracted and drowsy driving, as well as in-cabin and external risks. Nauto's predictive AI algorithms can assess, predict, and alert drivers of imminent risks to avoid collisions. It also provides real-time alerts to end distracted and drowsy driving, and self-guided coaching videos to help drivers improve their behavior. Nauto's claims management feature can quickly and reliably process and resolve claims, resulting in millions of dollars saved. Overall, Nauto is a comprehensive driver and vehicle safety platform that can help businesses reduce risk, improve safety, and save money.

Nestor is an AI-powered insurance assistant that provides clear and jargon-free answers to all your insurance questions. It can audit your insurance contracts, identify potential over-insurance or under-insurance, and suggest ways to improve your coverage. Nestor is constantly learning and can provide expert advice on a wide range of insurance topics.

Gradient AI is a leading provider of artificial intelligence solutions for the insurance industry. Its solutions improve loss ratios and profitability by predicting underwriting and claims risks with greater accuracy, as well as reducing quote turnaround times and claim expenses through intelligent automation.

VUW.ai is a unique virtual underwriting platform that offers end-to-end digital trading solutions for specialty insurance lines. The platform leverages machine learning to improve risk selection, reduce volatility, increase consistency, and enhance profitability and underwriting controls while lowering operating costs. VUW.ai aims to revolutionize the insurance market by providing a cost-effective and tech-based underwriting solution that caters to brokers and capacity providers. The platform also offers services in Property, Casualty, and Marine Cargo business, with plans to expand into other classes like Livestock, Fine Art, and Political Violence.

Binah.ai is an AI-powered Health Data Platform that offers a software solution for video-based vital signs monitoring. The platform enables users to measure various health and wellness indicators using a smartphone, tablet, or laptop. It provides support for continuous monitoring through a raw PPG signal from external sensors and offers a range of features such as blood pressure monitoring, heart rate variability, oxygen saturation, and more. Binah.ai aims to make health data more accessible for better care at lower costs by leveraging AI and deep learning algorithms.

BluePond GenAI PaaS is an automation and insights powerhouse tailored for Property and Casualty Insurance. It offers end-to-end execution support from GenAI data scientists, engineers & human-in-the-loop processing. The platform provides automated intake extraction, classification enrichment, validation, complex document analysis, workflow automation, and decisioning. Users benefit from rapid deployment, complete control of data & IP, and pre-trained P&C domain library. BluePond GenAI PaaS aims to energize and expedite GenAI initiatives throughout the insurance value chain.

Federato is an AI-powered platform that integrates Google Cloud's AI capabilities to provide new AI underwriting solutions for the insurance industry. It aims to revolutionize underwriting processes by leveraging AI technology to enhance risk assessment, portfolio management, and decision-making. Federato's RiskOps platform empowers underwriters with powerful insights, real-time risk selection guidance, and unified underwriting workflows, enabling them to make more informed decisions and improve operational efficiency.

Restb.ai is a leading provider of visual insights for real estate companies, utilizing computer vision and AI to analyze property images. The application offers solutions for AVMs, iBuyers, investors, appraisals, inspections, property search, marketing, insurance companies, and more. By providing actionable and unique data at scale, Restb.ai helps improve valuation accuracy, automate manual processes, and enhance property interactions. The platform enables users to leverage visual insights to optimize valuations, automate report quality checks, enhance listings, improve data collection, and more.

Sixfold is a risk assessment AI solution designed exclusively for insurance underwriters. The platform enhances underwriting efficiency, accuracy, and transparency for insurers, MGAs, and reinsurers. Sixfold's AI capabilities enable faster case reviews, appetite-aware risk insights, and data gathering from days to minutes. The application ingests underwriting guidelines, extracts risk data, and provides tailored risk insights to align with unique risk preferences. It offers customized solutions for various insurance lines and features intake prioritization, contextual risk insights, risk signal detection, inconsistency identification, and data summarization.

The AWS Generative AI Constructs Library is an open-source extension of the AWS Cloud Development Kit (AWS CDK) that provides multi-service, well-architected patterns for quickly defining solutions in code to create predictable and repeatable infrastructure, called constructs. The goal of AWS Generative AI CDK Constructs is to help developers build generative AI solutions using pattern-based definitions for their architecture. The patterns defined in AWS Generative AI CDK Constructs are high level, multi-service abstractions of AWS CDK constructs that have default configurations based on well-architected best practices. The library is organized into logical modules using object-oriented techniques to create each architectural pattern model.

Generative AI with LangChain is a code repository for building large language model (LLM) apps with Python, ChatGPT, and other LLMs. The repository provides code examples, instructions, and configurations for creating generative AI applications using the LangChain framework. It covers topics such as setting up the development environment, installing dependencies with Conda or Pip, using Docker for environment setup, and setting API keys securely. The repository also emphasizes stability, code updates, and user engagement through issue reporting and feedback. It aims to empower users to leverage generative AI technologies for tasks like building chatbots, question-answering systems, software development aids, and data analysis applications.

LearnOpenCV is a repository containing code for Computer Vision, Deep learning, and AI research articles shared on the blog LearnOpenCV.com. It serves as a resource for individuals looking to enhance their expertise in AI through various courses offered by OpenCV. The repository includes a wide range of topics such as image inpainting, instance segmentation, robotics, deep learning models, and more, providing practical implementations and code examples for readers to explore and learn from.

This repository is a curated list of awesome public object detection and recognition datasets. It includes a wide range of datasets related to object detection and recognition tasks, such as general detection and recognition datasets, autonomous driving datasets, adverse weather datasets, person detection datasets, anti-UAV datasets, optical aerial imagery datasets, low-light image datasets, infrared image datasets, SAR image datasets, multispectral image datasets, 3D object detection datasets, vehicle-to-everything field datasets, super-resolution field datasets, and face detection and recognition datasets. The repository also provides information on tools for data annotation, data augmentation, and data management related to object detection tasks.

Awesome-Segment-Anything is a powerful tool for segmenting and extracting information from various types of data. It provides a user-friendly interface to easily define segmentation rules and apply them to text, images, and other data formats. The tool supports both supervised and unsupervised segmentation methods, allowing users to customize the segmentation process based on their specific needs. With its versatile functionality and intuitive design, Awesome-Segment-Anything is ideal for data analysts, researchers, content creators, and anyone looking to efficiently extract valuable insights from complex datasets.

SurveyX is an advanced academic survey automation system that leverages Large Language Models (LLMs) to generate high-quality, domain-specific academic papers and surveys. Users can request comprehensive academic papers or surveys tailored to specific topics by providing a paper title and keywords for literature retrieval. The system streamlines academic research by automating paper creation, saving users time and effort in compiling research content.

This repository is part of Intelligent Document Processing with AWS AI Services workshop. It aims to automate the extraction of information from complex content in various document formats such as insurance claims, mortgages, healthcare claims, contracts, and legal contracts using AWS Machine Learning services like Amazon Textract and Amazon Comprehend. The repository provides hands-on labs to familiarize users with these AI services and build solutions to automate business processes that rely on manual inputs and intervention across different file types and formats.

Call Center AI is an AI-powered call center solution leveraging Azure and OpenAI GPT. It allows for AI agent-initiated phone calls or direct calls to the bot from a configured phone number. The bot is customizable for various industries like insurance, IT support, and customer service, with features such as accessing claim information, conversation history, language change, SMS sending, and more. The project is a proof of concept showcasing the integration of Azure Communication Services, Azure Cognitive Services, and Azure OpenAI for an automated call center solution.

The 'jobs' repository by comma.ai focuses on solving self-driving cars by building a robotics stack that includes state-of-the-art machine learning models, operating system design, hardware development, and manufacturing. The company aims to deliver constant incremental progress in self-driving technology to users, with a focus on practical solutions rather than hype. Job opportunities at comma.ai include technical challenges, phone screenings, and paid micro-internships, with perks such as chef-prepared meals, on-site gym access, and health insurance. The teams at comma.ai are organized into web, systems, infrastructure, product, design, and electrical engineering, with specific challenges for each team. The repository also offers opportunities for non-job seekers to participate in challenges and win prizes.

Skyvern automates browser-based workflows using LLMs and computer vision. It provides a simple API endpoint to fully automate manual workflows, replacing brittle or unreliable automation solutions. Traditional approaches to browser automations required writing custom scripts for websites, often relying on DOM parsing and XPath-based interactions which would break whenever the website layouts changed. Instead of only relying on code-defined XPath interactions, Skyvern adds computer vision and LLMs to the mix to parse items in the viewport in real-time, create a plan for interaction and interact with them. This approach gives us a few advantages: 1. Skyvern can operate on websites it’s never seen before, as it’s able to map visual elements to actions necessary to complete a workflow, without any customized code 2. Skyvern is resistant to website layout changes, as there are no pre-determined XPaths or other selectors our system is looking for while trying to navigate 3. Skyvern leverages LLMs to reason through interactions to ensure we can cover complex situations. Examples include: 1. If you wanted to get an auto insurance quote from Geico, the answer to a common question “Were you eligible to drive at 18?” could be inferred from the driver receiving their license at age 16 2. If you were doing competitor analysis, it’s understanding that an Arnold Palmer 22 oz can at 7/11 is almost definitely the same product as a 23 oz can at Gopuff (even though the sizes are slightly different, which could be a rounding error!) Want to see examples of Skyvern in action? Jump to #real-world-examples-of- skyvern

AI-powered call center solution with Azure and OpenAI GPT. The bot can answer calls, understand the customer's request, and provide relevant information or assistance. It can also create a todo list of tasks to complete the claim, and send a report after the call. The bot is customizable, and can be used in multiple languages.

Call Center AI is an AI-powered call center solution that leverages Azure and OpenAI GPT. It is a proof of concept demonstrating the integration of Azure Communication Services, Azure Cognitive Services, and Azure OpenAI to build an automated call center solution. The project showcases features like accessing claims on a public website, customer conversation history, language change during conversation, bot interaction via phone number, multiple voice tones, lexicon understanding, todo list creation, customizable prompts, content filtering, GPT-4 Turbo for customer requests, specific data schema for claims, documentation database access, SMS report sending, conversation resumption, and more. The system architecture includes components like RAG AI Search, SMS gateway, call gateway, moderation, Cosmos DB, event broker, GPT-4 Turbo, Redis cache, translation service, and more. The tool can be deployed remotely using GitHub Actions and locally with prerequisites like Azure environment setup, configuration file creation, and resource hosting. Advanced usage includes custom training data with AI Search, prompt customization, language customization, moderation level customization, claim data schema customization, OpenAI compatible model usage for the LLM, and Twilio integration for SMS.

This open hardware project aims to extend the life of Volvo P2 platform vehicles by updating them to current EU safety and emission standards. It involves designing and prototyping OEM hardware electronics that can replace existing electronics in these vehicles, using the existing wiring and without requiring reverse engineering or modifications. The project focuses on serviceability, maintenance, repairability, and personal ownership safety, and explores the advantages of using open solutions compared to conventional hardware electronics solutions.

This repository serves as a hub for Microsoft Official Build & Modernize AI Applications reference solutions and content. It provides access to projects demonstrating how to build Generative AI applications using Azure services like Azure OpenAI, Azure Container Apps, Azure Kubernetes, and Azure Cosmos DB. The solutions include Vector Search & AI Assistant, Real-Time Payment and Transaction Processing, and Medical Claims Processing. Additionally, there are workshops like the Intelligent App Workshop for Microsoft Copilot Stack, focusing on infusing intelligence into traditional software systems using foundation models and design thinking.

Arch is an intelligent Layer 7 gateway designed to protect, observe, and personalize LLM applications with APIs. It handles tasks like detecting and rejecting jailbreak attempts, calling backend APIs, disaster recovery, and observability. Built on Envoy Proxy, it offers features like function calling, prompt guardrails, traffic management, and standards-based observability. Arch aims to improve the speed, security, and personalization of generative AI applications.

The AI Data Science Team of Copilots is an AI-powered data science team that uses agents to help users perform common data science tasks 10X faster. It includes agents specializing in data cleaning, preparation, feature engineering, modeling, and interpretation of business problems. The project is a work in progress with new data science agents to be released soon. Disclaimer: This project is for educational purposes only and not intended to replace a company's data science team. No warranties or guarantees are provided, and the creator assumes no liability for financial loss.

LLMWare is a framework for quickly developing LLM-based applications including Retrieval Augmented Generation (RAG) and Multi-Step Orchestration of Agent Workflows. This project provides a comprehensive set of tools that anyone can use - from a beginner to the most sophisticated AI developer - to rapidly build industrial-grade, knowledge-based enterprise LLM applications. Our specific focus is on making it easy to integrate open source small specialized models and connecting enterprise knowledge safely and securely.

Insurance broker assistant for policy understanding.

Analyzes insurance documents with formal, friendly advice.

Expert in self-funded health plans, focusing on finance, stop loss, and data analytics.

Dansk vejledning i outsourcing regler for forsikringsselskaber

Conversational Actuary, blending examples with technical expertise.

Chat with your new personal insurance and claims assistant - you will only need to upload your insurance policy and he will tell you if you are covered for a specific event

I answer questions with the precision and expertise of an actuary.

Generates realistic worst-case scenarios in a thoughtful, detailed manner.

Formal yet witty AI & Insurance expert. Powered by Breebs (www.breebs.com)

Simulates and analyzes potential environmental disaster scenarios for preparedness.

Specializes in comparing insurance policies and providers.

Expert in explaining underwriting in finance and insurance.

A guide for exploring insurance options and resources.

Analyzes rare events with enhanced predictive capabilities.

Expert en code de la route français, précis sur choix multiples.

Professional, friendly insurance explainer

活泼友好的中国保险知识向导

Friendly and clear insurance advice expert

Map or simulate a scenario real time analyze probability of a life event coming true based on circumstances

Expert en documentation Solvabilité II