Picking the right platform to manage your large volume documents
EVERY TASK NEEDS A TOOL

VKG is a technology developed by LazarusAI that leverages advanced machine learning and computer vision techniques to construct comprehensive visual representations of knowledge domains. By integrating structured and unstructured data from various sources, VKG creates interconnected graphs that capture relationships, concepts, and entities within a domain. These visual knowledge graphs enable users to explore, analyze, and extract insights from complex datasets, facilitating informed decision-making and knowledge discovery.

ATLS is an advanced machine learning system developed by LazarusAI specifically designed for analyzing and modeling time series data. Utilizing state-of-the-art algorithms and techniques, ATLS can capture temporal patterns, trends, and dependencies within time series datasets, enabling accurate forecasting, anomaly detection, and predictive analytics. By leveraging ATLS, organizations can gain valuable insights into time-varying phenomena, optimize resource allocation, and make informed decisions based on predictive analytics.

RikAI is an AI-powered platform developed by LazarusAI that combines natural language processing (NLP), machine learning, and knowledge representation techniques to enable intelligent document understanding and processing. RikAI can analyze unstructured text documents, extract relevant information, and generate actionable insights, enhancing automation, efficiency, and accuracy in document-centric workflows. With its robust capabilities, RikAI empowers organizations to streamline document management, extract valuable insights, and make data-driven decisions.

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INSIGHTS IN INSURANCE

Published on
April 12, 2024

You Will Never Realize The Power of AI Until You Understand Generative AI vs. Extractive AI

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.

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Published on
April 12, 2024

Five Step Program to Get your Prompts into Shape

This 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.

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Published on
March 14, 2024

Coming Soon to a Screen Near You…A Prompt Engineer

Effective 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).

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Published on
April 12, 2024

Unusual View: Insurance AI Has to be Explainable. Period.

This 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.

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Published on
March 14, 2024

AI-Insights for Insurance: Conducting an Effective AI POC

This 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.

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Published on
March 14, 2024

Is there an Art & Science of Picking the Right Gen AI Solution to Handle your Documents?

The 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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INFINITE TOKEN CONTEXT WINDOW

Our cutting-edge technology ensures an infinite token context window, allowing our models to comprehend vast amounts of information with unparalleled depth and accuracy. With this capability, our AI systems can process data across diverse modalities and timeframes, empowering users with comprehensive insights and actionable intelligence.

<1% HALLUCINATION RATE

We build proprietary LLMs and VITs for information understanding, few-shot classification; and document segmentation, summarization, and extraction. We utilize both decoder only and encoder-decoder type transformers that range in size from 7 to 256 billion parameters.

NO TRAINING REQUIRED

A better way to store and search your data, VKGs are temporality enabled relational databases that exist in a multi-dimensional hyperspace and can allow for: semantic search, the addition of new information, and the creation of search citations to pinpoint relevant information.

KEY ADVANTAGES
THE NEXT GENERATION OF AI

Lazarus produces generative AI foundation models for document understanding. We apply artificial intelligence and computer vision to develop products and custom solutions that optimize the business processes of our clients in insurance, banking, and law. Organizations leverage our APIs to quickly and accurately get data out of their documents and directly to where it is needed most.

RESPONSIBLE MULTIMODAL AI

Our multimodal AI works with text, image, video, and time series data to enable rapid dataset enrichment and contextualization with fact based permissioning, low hallucination rates, citations, human bias correction, and on prem deployments.

ENTERPRISE GRADE FOUNDATION MODEL

We build proprietary LLMs and VITs for information understanding, few-shot classification; and document segmentation, summarization, and extraction. We utilize both decoder only and encoder-decoder type transformers that range in size from 7 to 256 billion parameters.

VECTOR KNOWLEDGE GRAPH

A better way to store and search your data, VKGs are temporality enabled relational databases that exist in a multi-dimensional hyperspace and can allow for: semantic search, the addition of new information, and the creation of search citations to pinpoint relevant information.

<<NO TRAINING REQUIRED>>

<<NO TRAINING REQUIRED>>

<<NO TRAINING REQUIRED>>

<<NO TRAINING REQUIRED>>

<<NO TRAINING REQUIRED>>