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Description
Graphwise is an advanced AI platform designed to assist businesses in automating their knowledge processes while ensuring confidence in their AI systems by converting disparate data into a reliable semantic foundation. This comprehensive suite enhances the reliability and scalability of generative AI by transforming raw data into contextually rich, AI-compatible assets, implementing intelligent agent-based frameworks, and offering robust AI applications within a cohesive platform. By utilizing Precise GraphRAG, Graphwise transcends mere data fragments, leveraging a governed knowledge graph to anchor every response in established facts, thereby removing inaccuracies and delivering precise, actionable insights. The platform integrates automated modeling, cutting-edge graph technology, semantic search, recommendation systems, taxonomy and ontology management, data automation, graph-centric text mining, and enterprise-ready GraphRAG workflows. Suitable for a variety of applications, it addresses challenges in technical knowledge management, semantic digital twins, compliance intelligence, and scientific knowledge management, showcasing its versatility across numerous business needs. Additionally, Graphwise's innovative approach ensures that organizations can achieve a deeper understanding of their data, ultimately leading to informed decision-making and enhanced operational efficiency.
Description
At Iris.ai we have spent the last 6 years building an award-winning AI engine for scientific text understanding. Our algorithms for text similarity, tabular data extraction, domain-specific entity representation learning and entity disambiguation and linking measure up to the best in the world. On top of that, our machine builds a comprehensive knowledge graph containing all entities and their linkages to allow humans to learn from it, use it and also give feedback to the system.
The Iris.ai Researcher Workspace is a flexible tool suite that allows to approach a project in a variety of ways. Modules include content based explorative search, machine analysis of document sets, extracting and systematizing data points, automatically writing summaries of multiple documents - and very powerful filters based on context descriptions, the machine’s analysis, or specific data points or entities. The Iris.ai engine for scientific text understanding is a powerful interdisciplinary system that can be automatically reinforced on a specific research field for much more nuanced machine understanding - without human training or annotation.
API Access
Has API
API Access
Has API
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Graphwise
Country
Bulgaria
Website
graphwise.ai/
Vendor Details
Company Name
Iris.ai
Founded
2015
Country
Norway
Website
iris.ai/
Product Features
Data Management
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge
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
Product 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