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What is Nextnet?

Stop spending your valuable time navigating through countless databases or dealing with the complexities of various data formats and intricate queries. Instead, channel your energy into leveraging your intuition and expert knowledge to discover critical insights and follow captivating scientific avenues. We are excited to introduce Nextnet, an innovative digital platform that integrates the most recent breakthroughs in natural language processing, transparent artificial intelligence, software solutions, graph databases, and human-in-the-loop reinforcement learning to accelerate the pace of scientific research and development. Our mission is to compile the most comprehensive, human-curated dataset for reinforcement learning, aimed at exploring the relationships between scientific disciplines. With Sapiens’ integrated search interface, you can effortlessly tap into and connect with knowledge spread across diverse data sources. This not only enables you to search for well-known topics via a simple query but also allows you to delve into lesser-known subjects through our sophisticated conceptual search within an enduring knowledge network. By making use of these advanced tools, researchers can significantly boost their comprehension and foster innovation like never before, empowering them to make groundbreaking discoveries. Through collaboration and the sharing of insights, the potential for scientific advancement is limitless.

What is Iris.ai?

At Iris.ai, we have dedicated the past six years to developing an award-winning AI engine that excels in comprehending scientific texts. Our state-of-the-art algorithms for text similarity, extraction of tabular data, learning domain-specific entity representations, and entity disambiguation and linking rank among the finest globally. Additionally, our machine constructs an extensive knowledge graph that encompasses all entities and their interconnections, enabling users to learn from it, utilize it, and also provide feedback to enhance the system further. The Iris.ai Researcher Workspace offers a versatile suite of tools that enables users to tackle projects from multiple perspectives. Its modules feature content-driven exploratory searches, analytical assessments of document collections, systematic extraction and organization of data points, automated summarization of various documents, and highly effective filters based on context descriptions, machine analyses, or targeted data points and entities. Furthermore, the Iris.ai engine for scientific text understanding is a robust interdisciplinary platform that can be automatically fine-tuned for specific research domains, allowing for a deeper machine comprehension without the need for human training or annotation, ultimately streamlining the research process.

Media

Media

Integrations Supported

Liberate

Integrations Supported

Liberate

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Nextnet

Company Location

United States

Company Website

getnextnet.com/product/

Company Facts

Organization Name

Iris.ai

Date Founded

2015

Company Location

Norway

Company Website

iris.ai/

Categories and Features

Categories and Features

Data Extraction

Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction

Natural Language Processing

Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization

Qualitative Data Analysis

Annotations
Collaboration
Data Visualization
Media Analytics
Mixed Methods Research
Multi-Language
Qualitative Comparative Analysis
Quantitative Content Analysis
Sentiment Analysis
Statistical Analysis
Text Analytics
User Research Analysis

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