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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 RoeAI?
Utilize AI-Powered SQL to effectively extract, categorize, and implement Retrieval-Augmented Generation (RAG) across various types of media, such as documents, websites, videos, images, and audio files. In the realms of finance and insurance, a staggering 90% of information is found in PDF format, which poses significant hurdles due to the complexity of embedded tables, charts, and graphics. Roe provides the capability to transform large collections of financial documents into organized data and semantic embeddings, allowing for seamless integration with your preferred chatbot. Historically, the detection of fraudulent activities has been a predominantly semi-manual endeavor, hindered by the wide variety of document formats that are challenging for humans to assess effectively. With RoeAI, you can develop robust AI-driven tagging systems for millions of documents, identification numbers, and videos, significantly enhancing the speed and accuracy of data processing and fraud detection. This cutting-edge solution not only optimizes the identification process but also substantially improves the overall management and utilization of data resources. As a result, organizations can expect increased operational efficiency and better outcomes in their analytical efforts.
Integrations Supported
ATLAS.ti
MAXQDA
NVivo
API Availability
Has API
API Availability
Has API
Pricing Information
$0
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
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
RoeAI
Date Founded
2023
Company Location
United States
Company Website
www.getroe.ai
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
Data Extraction
Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction
Data Warehouse
Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge