Organizations struggle to efficiently process and extract insights from the increasing volumes of complex, unstructured data across various formats like text, images, audio, and tabular data. Traditional methods of data extraction and analysis are often time-consuming, inaccurate, and require significant manual effort. This makes it difficult to leverage valuable information for timely decision-making.

Lazarus provides a suite of multimodal AI foundation models and tools designed for document understanding and data extraction across diverse formats. Their AI-powered platform, including RikAI, VKG, and ATLS, enables automated data extraction, reasoning, and knowledge graph construction. The platform orchestrates AI models to process data without input limitations, delivering explainable and actionable insights. By integrating these models, users can securely embed their own private data, keeping knowledge up-to-date and improving accuracy beyond traditional methods.

RikAI: Multi-modal Large Language Models (LLMs) designed for document understanding and multi-modal reasoning, ensuring security, accuracy, and effectiveness.

VKG (Vector Knowledge Graphs): Integrates with RikAI models to embed private data securely, keeping knowledge up-to-date and surpassing Retrieval-Augmented Generation (RAG) methods.

ATLS: Orchestrates other AI models and tools to process large amounts of disconnected data in various formats, filtering noise and turning everything into clear, actionable insights.

Multimodality: Handles multiple data formats, including text, images, audio, video, tabular, time series, signal, and geospatial data.

Routing Models: Tool-selection model selects the right tool for the right data at the right layer, presenting concise information outputs.

No Token Input Limit: Processes large volumes of data without input limitations, enabling comprehensive understanding and reliable conclusions.

Primarily Extractive Models: Extracts key insights and information from large volumes of data quickly and efficiently.

Temporality Understanding: Understands time or chronology via iterative fine-tuning with temporal information and tasks that require temporal reasoning.

2-Dimensional Understanding: Analyzes information presented in two dimensions, such as tables and charts.

Counterfactuals as Metadata: Leverages counterfactuals in LLMs + a vector knowledge graph to provide insights into what is possible, plausible, not plausible, and impossible.

Lazarus primarily serves organizations in the insurance and government sectors that require efficient and accurate data extraction, classification, and analysis from complex documents and data sources.