Axion™
AI-powered data ingestion and processing for R&D workflows.
Executive Summary
Axion™ is a key component of the Iris.ai Researcher Workspace, an AI Retrieval & Evaluation Platform tailored for enterprise R&D. It helps organizations deploy secure, high-quality Agentic AI by simplifying data ingestion, orchestration, retrieval, and evaluation through tailored workflows at scale. The platform is specifically designed to streamline research document processing for R&D-heavy industries such as chemistry, pharmaceuticals, MedTech, material science, and biotech. By offering advanced search strategies and context-enhanced AI, Axion™ within the Researcher Workspace enables efficient literature reviews, patent research, and overall innovation, transforming how extensive datasets are managed and utilized in research and development.
Use Cases
- Streamlining literature reviews for scientific research
- Revolutionizing patent research with AI tools
- Managing and navigating extensive R&D datasets
- Searching millions of documents to find relevant information
- Integrating advanced document retrieval with large language models (LLMs)
Features
Intelligence
- AI Retrieval & Evaluation Platform: Tailored for enterprise to deploy secure, high-quality Agentic AI for R&D workflows.
- Context-Enhanced AI (RAG): Integrates advanced document retrieval with large language models using RAG as a Service for deeper contextual understanding.
- Streamlined Search Strategies: Offers efficient and advanced search capabilities to manage and navigate extensive datasets effectively.
Technical Specifications
- Deployment
- SaaS
AI/ML Stack
- RAG (Retrieval Augmented Generation)
Integrations
- Google Drive
- Dropbox
- Microsoft SharePoint
Pricing
- Starting Price
- Contact sales
- Target Customer
- Enterprise
- Free Trial
- Yes
About Iris.ai Researcher Workspace
Iris.ai is a Norwegian company specializing in AI-driven tools for scientific research and enterprise R&D. It offers an AI platform designed to streamline literature reviews, data extraction, and document summarization, focusing on agentic RAG AI workflows to enhance factuality and efficiency in research and development. Founded in 2015, Iris.ai collaborates with universities and corporate clients to foster open science and innovation.
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