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The cognitive center of ATLS, responsible for orchestrating complex decision-making.
Copyright © 2024 Lazarus Enterprises Inc.
All rights reserved.
Our models rely on the inputs they are given and tuned only to answer when it finds reliable data to substantiate.
There is no “black box” in our process. All of our outputs provide explainability metrics and auditable context.
Our solutions can be deployed behind your firewall. The data you put through and what you do with it is your business alone.
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RikAI2 Capabilities
Risk Underwriting
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“Took me about 3 days to get something working for benefits summaried. Haven’t had to touch it since. (it’s been running for 12+ months)”
—CTO
Insurance Brokerage
“Around 80% of the time our claims handlers preferred your summaries over physician generated ones. (We tied most of the rest of the time)."
—CIO
Top 5 Life Insurer
“With three days of prompting, without trying to optimize prompts, we were able to eliminate 6 weeks of engineering work in what would typically be a 3 month process.”
—Senior Data Scientist
Large Worker's Compensation Carrier
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Accuracy in automating data extraction and classification in 8 weeks
Advanced review including risk rating of entire portfolios in M&A deals, resulting in ~10X ROI
Reduced disability claims end-to-end processing to from 2-3 weeks to 30 mins
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October 11, 2024
In partnership with our customer, a leading US Insurance company, we engineered an AI first data processing workflow by automating data extraction and signature verification. With over 97% accuracy and confidence levels, this solution allows staff to focus on high-value tasks, showcasing the transformative power of AI in the insurance industry.
Read moreOctober 11, 2024
Discover how Lazarus AI accelerated claims processing for a leading US Life Insurance company by reducing time-sensitive claim handling from 30 days to just 30 minutes. By seamlessly integrating advanced AI technology into existing systems, Lazarus AI enhanced accuracy and efficiency, mitigating reputational and regulatory risks while improving customer satisfaction.
Read moreOctober 11, 2024
A reinsurance company leveraged Lazarus AI to identify critical data anomalies during a potential acquisition. By integrating seamlessly with existing tools, Lazarus AI revealed significant under-reserving issues, saving the company from unforeseen liabilities. This case study highlights the power of AI in enhancing due diligence and ensuring data quality, providing a competitive edge in the insurance industry.
Read moreOctober 11, 2024
Our team helped redesign underwriting for a top US life insurer by leveraging advanced AI models to refine risk assessment. By identifying nuanced patterns in medical data, the insurer was able to accurately price premiums and approve previously rejected applications, enhancing profitability and underwriting quality.
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The difference between generative AI and extractive AI is straightforward. Yet, Lazarus AI still sees these approaches confused on a daily basis. This confusion prevents companies from getting real value out of AI and creates misconceptions about the viability of enterprise AI solutions. Both approaches are powerful and both have uses in the modern corporation. Misusing one of these approaches is like misusing any other tool: it can lead to endless frustrations and inefficiencies.
Read moreThis Insight presents five steps needed for success in the world of prompting. As noted earlier, prompting is both art and science and prompting will continue to evolve quickly. Following the Steps and guidance here will maximize probability of success and ignoring the guidance here will increase risk, money, and time. Continue to watch Lazarus for Insights as this evolution occurs.
Read moreEffective prompting is a vital component of implementing LLM solutions in the insurance industry. To keep up with the current state of AI technology, insurers should look to develop their prompt engineering capabilities in 2024. Knowledge workers across all domains will need to learn prompting skills to effectively use LLM-based tools (general prompting). Dedicated prompt engineering professionals will not disappear, rather their responsibilities will shift towards large-scale and specialized prompting tasks (enterprise prompting).
Read moreThis insight presents a perspective on the concept of Explainability in AI. This topic will be of intense interest while both State and Federal authorities work through the rules of the road. In the interim, insurers need to strive for explainability and hold their partners accountable.
Read moreThis Insight leverages Lazarus AI’s experience in the insurance industry to present a simple framework for conducting an effective POC. Many insurers have successfully completed a POC and implemented AI technology in production. In the coming year, many more will. We at Lazarus AI are available to help you whether you are just starting to develop use cases or are ready to dive into a POC of your own.
Read moreThe decision between a point solution and a platform depends on your organization’s specific needs, budget constraints, and long-term vision. Assess the trade-offs in terms of functionality, ease of implementation, scalability, and integration capabilities to make the most appropriate choice for your document understanding needs.
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