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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 Restructured?

Restructured is a cutting-edge platform that harnesses the power of artificial intelligence to help businesses extract valuable insights from large volumes of unstructured data. It adeptly manages diverse formats such as documents, images, audio, and video by combining advanced language model functionalities with refined search and retrieval methods, enabling it to index and understand information in context. Through the transformation of substantial datasets into actionable insights, Restructured facilitates easier navigation and analysis of complex data, ultimately optimizing decision-making processes. Consequently, organizations are better equipped to react promptly and accurately to new trends and challenges, thereby gaining a competitive edge in their respective markets. This innovative approach not only streamlines operations but also empowers companies to make informed choices that drive growth and efficiency.

Media

Media

No images available

Integrations Supported

ATLAS.ti
MAXQDA
NVivo

Integrations Supported

API Availability

API Availability

Pricing Information

$0
Free Version

Pricing Information

$99/user/month

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub
Webinars
Online Training

Company Facts

Organization Name

Skimle

Date Founded

2025

Company Location

Finland

Company Website

www.skimle.com

Company Facts

Organization Name

Kolena

Date Founded

2022

Company Location

United States

Company Website

www.kolena.com/restructured/

Categories and Features

Qualitative Data Analysis

Collaboration
Data Visualization
Multi-Language
Qualitative Comparative Analysis
Sentiment Analysis
Text Analytics
User Research Analysis

Categories and Features

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