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Log10 for Insurance

Log10 for Insurance

Transforming Insurance with AI Precision.

Transforming Insurance with AI Precision.

Define and attain crucial LLM accuracy targets in insurance with AI-powered LLMOps & Observability.

Define and attain crucial LLM accuracy targets in insurance with AI-powered LLMOps & Observability.

Define and attain crucial LLM accuracy targets in insurance with AI-powered LLMOps & Observability.

Define and attain crucial LLM accuracy targets in insurance with AI-powered LLMOps & Observability.

LLMs are revolutionizing insurance

Insurance companies are leveraging Large Language Models (LLMs) in key areas to improve efficiency, enhance products, and deliver better services. 

Insurance companies are leveraging Large Language Models (LLMs) in key areas to improve efficiency, enhance products, and deliver better services. 

Insurance companies are leveraging Large Language Models (LLMs) in key areas to improve efficiency, enhance products, and deliver better services. 

01

Chatbot Q&A Systems

LLM-driven chatbot question-and-answer systems provide instant, accurate responses to user inquiries, facilitating efficient data collection and analysis for underwriting and claims processes.

01

Chatbot Q&A Systems

LLM-driven chatbot question-and-answer systems provide instant, accurate responses to user inquiries, facilitating efficient data collection and analysis for underwriting and claims processes.

01

Chatbot Q&A Systems

LLM-driven chatbot question-and-answer systems provide instant, accurate responses to user inquiries, facilitating efficient data collection and analysis for underwriting and claims processes.

01

Chatbot Q&A Systems

LLM-driven chatbot question-and-answer systems provide instant, accurate responses to user inquiries, facilitating efficient data collection and analysis for underwriting and claims processes.

02

Underwriting, Risk Assessment & Pricing Optimization

LLMs enhance underwriting, risk assessment, and pricing optimization by analyzing historical data and market trends, empowering actuaries and underwriters to make informed decisions and develop competitive pricing strategies.

02

Underwriting, Risk Assessment & Pricing Optimization

LLMs enhance underwriting, risk assessment, and pricing optimization by analyzing historical data and market trends, empowering actuaries and underwriters to make informed decisions and develop competitive pricing strategies.

02

Underwriting, Risk Assessment & Pricing Optimization

LLMs enhance underwriting, risk assessment, and pricing optimization by analyzing historical data and market trends, empowering actuaries and underwriters to make informed decisions and develop competitive pricing strategies.

02

Underwriting, Risk Assessment & Pricing Optimization

LLMs enhance underwriting, risk assessment, and pricing optimization by analyzing historical data and market trends, empowering actuaries and underwriters to make informed decisions and develop competitive pricing strategies.

03

Claims Management, Billing, & Policy Generation

LLMs automate the claims process, enhance billing accuracy, and streamline policy generation by synthesizing information from various sources, reducing manual workload and improving efficiency.

03

Claims Management, Billing, & Policy Generation

LLMs automate the claims process, enhance billing accuracy, and streamline policy generation by synthesizing information from various sources, reducing manual workload and improving efficiency.

03

Claims Management, Billing, & Policy Generation

LLMs automate the claims process, enhance billing accuracy, and streamline policy generation by synthesizing information from various sources, reducing manual workload and improving efficiency.

03

Claims Management, Billing, & Policy Generation

LLMs automate the claims process, enhance billing accuracy, and streamline policy generation by synthesizing information from various sources, reducing manual workload and improving efficiency.

04

Fraud Detection

LLMs enhance fraud detection capabilities by analyzing patterns in textual data, improving accuracy in identifying fraudulent activities.

04

Fraud Detection

LLMs enhance fraud detection capabilities by analyzing patterns in textual data, improving accuracy in identifying fraudulent activities.

04

Fraud Detection

LLMs enhance fraud detection capabilities by analyzing patterns in textual data, improving accuracy in identifying fraudulent activities.

04

Fraud Detection

LLMs enhance fraud detection capabilities by analyzing patterns in textual data, improving accuracy in identifying fraudulent activities.

05

Regulatory Compliance

LLMs assist in automating compliance processes by analyzing legal documents and ensuring adherence to regulatory requirements, minimizing risks and manual efforts.

05

Regulatory Compliance

LLMs assist in automating compliance processes by analyzing legal documents and ensuring adherence to regulatory requirements, minimizing risks and manual efforts.

05

Regulatory Compliance

LLMs assist in automating compliance processes by analyzing legal documents and ensuring adherence to regulatory requirements, minimizing risks and manual efforts.

05

Regulatory Compliance

LLMs assist in automating compliance processes by analyzing legal documents and ensuring adherence to regulatory requirements, minimizing risks and manual efforts.

06

Cyber & AI Insurance

LLM-based feedback models provide an independent way for insurance companies to evaluate risk from AI inaccuracies or hallucinations when underwriting cyber or AI insurance policies.

06

Cyber & AI Insurance

LLM-based feedback models provide an independent way for insurance companies to evaluate risk from AI inaccuracies or hallucinations when underwriting cyber or AI insurance policies.

06

Cyber & AI Insurance

LLM-based feedback models provide an independent way for insurance companies to evaluate risk from AI inaccuracies or hallucinations when underwriting cyber or AI insurance policies.

06

Cyber & AI Insurance

LLM-based feedback models provide an independent way for insurance companies to evaluate risk from AI inaccuracies or hallucinations when underwriting cyber or AI insurance policies.

Consequence

The chatbot collects sensitive information without proper data protection, leading to a potential data breach. This could result in regulatory fines and damage to the company's reputation.

The problem

The problem

LLM errors and hallucinations can lead to significant risks

LLMs can produce unreliable results that provide incorrect advice or disclose sensitive information leading to privacy violations. Human oversight guarantees accuracy and safety, but it’s impossible to manually evaluate thousands or millions of LLM completions each day.

LLMs can produce unreliable results that provide incorrect advice or disclose sensitive information leading to privacy violations. Human oversight guarantees accuracy and safety, but it’s impossible to manually evaluate thousands or millions of LLM completions each day.

LLMs can produce unreliable results that provide incorrect advice or disclose sensitive information leading to privacy violations. Human oversight guarantees accuracy and safety, but it’s impossible to manually evaluate thousands or millions of LLM completions each day.

Our solution

Our solution

Get human-accurate LLM oversight with customized models

Log10 AutoFeedback evaluation models detect errors and reduce risk by instantly reviewing LLM completions with the accuracy of a human. Inspired by interpretability research and using latent space technology, Log10 AutoFeedback offers accuracy comparable to fine-tuned models and surpasses LLM-as-a-judge, all while needing far fewer samples for faster, more efficient deployment.

90% less data needed; start with just 20-30 human samples

90% less data needed; start with just 20-30 human samples

90% less data needed; start with just 20-30 human samples

90% less data needed; start with just 20-30 human samples

Highly customizable for specific tasks and domains

Highly customizable for specific tasks and domains

Highly customizable for specific tasks and domains

Highly customizable for specific tasks and domains

Lightning-fast: <100ms latency

Lightning-fast: <100ms latency

Lightning-fast: <100ms latency

Lightning-fast: <100ms latency

Cheaper: leverages compact models vs. GPT-scale ones

Cheaper: leverages compact models vs. GPT-scale ones

Cheaper: leverages compact models vs. GPT-scale ones

Cheaper: leverages compact models vs. GPT-scale ones

Versatile: supports agentic & multimodal evals

Versatile: supports agentic & multimodal evals

Versatile: supports agentic & multimodal evals

Versatile: supports agentic & multimodal evals

Ideal for on-prem deployment

Ideal for on-prem deployment

Ideal for on-prem deployment

Ideal for on-prem deployment

Log10 AutoFeedback models are faster, cheaper, and require minimal data. Zero-shot prompting is quick but often lacks accuracy, while fine-tuned models are precise but demand significant resources. Log10 AutoFeedback combines the best of both, offering accuracy comparable to fine-tuned models and surpassing LLM-as-a-judge, all while needing far fewer samples for faster, more efficient deployment.

By labeling each and every LLM completion with human-accurate feedback, AutoFeedback powers observability, workflow, and automation features that enable developers to set and hit critical reliability goals for insurance AI applications.

By labeling each and every LLM completion with human-accurate feedback, AutoFeedback powers observability, workflow, and automation features that enable developers to set and hit critical reliability goals for insurance AI applications.

By labeling each and every LLM completion with human-accurate feedback, AutoFeedback powers observability, workflow, and automation features that enable developers to set and hit critical reliability goals for insurance AI applications.

Monitoring & Alerting

Set quality threshold targets and understand exactly how your application is performing. Get alerts when quality falls below critical thresholds.

Ranking & Triaging

Errors are automatically prioritized and queued for resolution. Engineers debug and resolve issues using the Log10 LLMOps Observability Stack.

Self-Improving Applications

Datasets curated with feedback automatically tune prompts and models, continuously improving accuracy while in production.

Want to know more? We’ve got you covered.

Want to know more? We’ve got you covered.

Want to know more? We’ve got you covered.

Want to know more? We’ve got you covered.