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AI-Powered Platform Enhancement for Scientific Text Understanding

beetroot

Information technology

Health & Fitness

Adoption Barrier for AI/ML Tools

Iris.ai faced challenges with user adoption of its AI/ML tools within the scientific research field. The existing platform needed improvements to enhance user experience, data processing capabilities, and overall usability to facilitate research document processing, data extraction, analysis, and summarization.

About the Client

Iris.ai is an AI and machine learning company developing language models for research organizations and material science companies, focusing on accelerating R&D processes.

Project Goals

Improve user experience and ease of use of the Researcher Workspace platform.
Enhance the platform's ability to process and analyze large scientific document sets.
Increase user engagement and adoption of AI/ML features within the platform.
Scale the platform to accommodate growing user base and data volume.
Maintain client control over the project development process while ensuring requirements are met.

Functional Requirements

Concept-based search of research papers.
Automated data extraction from scientific documents.
Systematization and organization of extracted data.
Analysis of large document sets.
AI-powered document summarization.
User-friendly interface for all platform functionalities.
Mobile application access to core features.

Preferred Technologies

Angular

Docker

Flask

Python

Vue.js

JavaScript

React

PostgreSQL

MongoDB

Node.js

GraphQL

Integrations Required

Potential integration with external data sources (e.g., scientific databases).
Integration with user authentication systems.

Key Non-Functional Requirements

Scalability to handle increasing data volume and user traffic.
High performance for fast document processing and analysis.
Robust security measures to protect sensitive research data.
Maintainability and ease of updates.

Expected Business Impact

Successful completion of this project will result in increased user adoption of Iris.ai's platform, faster R&D cycles for clients, enhanced competitiveness in the AI/ML market, and improved customer satisfaction. It will also solidify Iris.ai's position as a leader in AI-powered scientific text understanding.