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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 Delve?

Software designed for qualitative data analysis includes CAQDAS, which is essential for coding within qualitative research. Collaborating with your team, you can effectively analyze transcripts from both focus groups and in-depth interviews using this tool. Delve is another platform that specializes in qualitative data analysis and is known for its user-friendly interface. This online software facilitates teamwork in qualitative analysis, enabling you to uncover valuable human insights rapidly. With Delve, researchers can produce comprehensive reports that maintain a quick turnaround without compromising on depth or quality. The ability to collaborate seamlessly and gain insights efficiently makes Delve a valuable asset in qualitative research endeavors.

Media

Media

Integrations Supported

ATLAS.ti
MAXQDA
NVivo
NationBuilder
iFinder

Integrations Supported

ATLAS.ti
MAXQDA
NVivo
NationBuilder
iFinder

API Availability

Has API

API Availability

Has API

Pricing Information

$0
Free Trial Offered?
Free Version

Pricing Information

$50 per user per month
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

Skimle

Date Founded

2025

Company Location

Finland

Company Website

www.skimle.com

Company Facts

Organization Name

Delve

Date Founded

2017

Company Location

United States

Company Website

delvetool.com

Categories and 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

Categories and 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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