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Description

OpenText™, Unstructured Data Analytics Products use AI and machine learning in order to help organizations discover and leverage key insights that are hidden deep within unstructured data such as text, audio, videos, and images. Organizations can connect their data at scale to understand the context and content locked in high-growth, unstructured content. Unified text, speech and video analytics support over 1,500 data formats to help you uncover insights within all types media. Use OCR, natural language processing and other AI models to track and understand the meaning of unstructured data. Use the latest innovations in deep neural networks and machine learning to understand spoken and written language in data. This will reveal greater insights.

Description

Skimle revolutionizes the way unstructured qualitative data is converted into structured, analyzable datasets through the use of artificial intelligence. In contrast to RAG chatbots that simply retrieve isolated excerpts, Skimle meticulously processes complete sets of documents from the outset—examining each segment, gathering insights, and categorizing them within a structured hierarchy of themes. You can upload various formats of qualitative data such as interview transcripts, PDFs, audio or video files, and reports. The workflow that Skimle employs, which draws inspiration from scholarly thematic analysis, systematically codes every passage, uncovers recurring patterns, and compiles a comprehensive "spreadsheet" where documents are organized as rows and themes as columns. Each insight is directly tied to verified quotes, ensuring accuracy without any fabrication. Supporting over 100 languages and capable of handling more than 1,000 documents per project, Skimle is fully compliant with GDPR regulations applicable in the EU, providing complete traceability between themes and quotes. Users can also enjoy features such as customizable categories, AI-driven chat for reasoning, and options to export findings into Word, Excel, or PowerPoint formats. What sets Skimle apart is its ability to merge the rigorous standards of academic research with the rapid processing capabilities of AI. Tasks that traditionally consume weeks when using NVivo or other conventional tools can be completed in mere hours with Skimle, all while maintaining detailed audit trails essential for peer review and validation. This efficiency not only saves time but enhances the overall research experience, making qualitative analysis more accessible and streamlined than ever before.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

ATLAS.ti
Azure Marketplace
MAXQDA
NVivo

Integrations

ATLAS.ti
Azure Marketplace
MAXQDA
NVivo

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

$0
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

OpenText

Founded

1991

Country

Canada

Website

www.opentext.com/products/unstructured-data-analytics

Vendor Details

Company Name

Skimle

Founded

2025

Country

Finland

Website

www.skimle.com

Product Features

Artificial Intelligence

Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)

Business Intelligence

Ad Hoc Reports
Benchmarking
Budgeting & Forecasting
Dashboard
Data Analysis
Key Performance Indicators
Natural Language Generation (NLG)
Performance Metrics
Predictive Analytics
Profitability Analysis
Strategic Planning
Trend / Problem Indicators
Visual Analytics

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Enterprise Search

AI / Machine Learning
Faceted Search / Filtering
Full Text Search
Fuzzy Search
Indexing
Text Analytics
eDiscovery

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

Text Mining

Boolean Queries
Document Filtering
Graphical Data Presentation
Language Detection
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis
Topic Clustering

Product Features

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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