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What is Skimle?
Skimle transforms the process of turning unstructured qualitative data into structured and analyzable datasets through advanced artificial intelligence techniques. Unlike RAG chatbots that merely fetch unrelated snippets, Skimle diligently processes entire document collections from the beginning—assessing each section, extracting insights, and organizing them into a well-defined thematic hierarchy.
Users can upload a variety of qualitative data formats, including interview transcripts, PDFs, audio or video recordings, and reports. The approach Skimle adopts, inspired by rigorous thematic analysis, systematically codes every text segment, identifies recurring themes, and creates a detailed "spreadsheet" that arranges documents as rows and themes as columns. Each insight is meticulously linked to verified quotes, guaranteeing that the information presented is accurate and free from any fabrication.
With support for over 100 languages and the ability to manage more than 1,000 documents in a single project, Skimle adheres strictly to GDPR regulations relevant in the EU, ensuring thorough traceability between themes and their associated quotes. Additionally, users benefit from customizable category options, AI-enhanced chat for rationale, and the ability to export results into Word, Excel, or PowerPoint formats.
What distinguishes Skimle is its unique capability to combine the rigorous methodologies of academic research with the swift processing power of artificial intelligence. Tasks that typically take weeks to complete using NVivo or similar traditional tools can be accomplished in just a few hours with Skimle, all while providing essential audit trails necessary for peer review and validation. This remarkable efficiency not only conserves valuable time but also significantly improves the overall qualitative research experience, making it more accessible and streamlined than has ever been possible before. Furthermore, Skimle’s innovative approach enhances the quality of research outputs, allowing researchers to focus on deriving meaningful conclusions from their data rather than getting bogged down in the analytical process.
What is Quirkos?
Quirkos offers a user-friendly, affordable, and visual approach to the qualitative analysis of text data. Its distinct bubble interface enhances usability, providing users with immediate and intuitive insights. The platform facilitates live collaboration, enables side-by-side comparisons, and features powerful visualizations that help reveal intriguing discoveries. Additionally, Quirkos is accessible as both cloud-based and offline software, ensuring consistent functionality across Windows, Mac, and Linux operating systems. This versatility makes it a valuable tool for researchers and analysts alike.
Integrations Supported
API Availability
API Availability
Pricing Information
$0
Free Version
Pricing Information
$6 per user per month
One-off student licences from $69, or $6 a month.
Free Trial Offered?
Supported Platforms
SaaS
On-Prem
Supported Platforms
SaaS
Windows
Mac
Linux
Customer Service / Support
Web-Based Support
Customer Service / Support
Standard Support
Web-Based Support
Training Options
Documentation Hub
Online Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Skimle
Date Founded
2025
Company Location
Finland
Company Website
www.skimle.com
Company Facts
Organization Name
Quirkos
Date Founded
2014
Company Location
United Kingdom
Company Website
www.quirkos.com
Categories and Features
Qualitative Data Analysis
Collaboration
Data Visualization
Multi-Language
Qualitative Comparative Analysis
Sentiment Analysis
Text Analytics
User Research Analysis
Unstructured Data Analysis
Not specified
Categories and Features
Data Visualization
Analytics
Filtered Views
OLAP
Relational Display
Visual Discovery
Higher Education
Not specified
Market Research
Data Management
Qualitative Data Analysis
Annotations
Collaboration
Data Visualization
Mixed Methods Research
Multi-Language
Qualitative Comparative Analysis
Text Analytics
User Research Analysis