TILDEielab
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About
Skimle transforms unstructured qualitative data into structured, analyzable datasets using AI. Unlike RAG chatbots that retrieve random passages, Skimle systematically processes entire document sets upfront—analyzing each section, extracting insights, and organizing them into hierarchical theme taxonomies.
Upload interview transcripts, PDFs, audio/video, reports, or any qualitative data. Skimle's worklow (inspired by academic thematic analysis) codes every passage, identifies patterns, and creates a "spreadsheet" where documents are rows and themes are columns. Every insight links to verified quotes - no hallucinations.
100+ languages, 1,000+ docs/project, GDPR-compliant EU storage, full traceability (themes↔quotes), editable categories, AI reasoning chat, export to Word/Excel/PowerPoint reports etc.
Why different: Combines academic-grade rigor with AI speed. What takes weeks in NVivo or other legacy tools takes hours in Skimle, with full audit trails for peer review.
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About
TILDE (Term Independent Likelihood moDEl) is a passage re-ranking and expansion framework built on BERT, designed to enhance retrieval performance by combining sparse term matching with deep contextual representations. The original TILDE model pre-computes term weights across the entire BERT vocabulary, which can lead to large index sizes. To address this, TILDEv2 introduces a more efficient approach by computing term weights only for terms present in expanded passages, resulting in indexes that are 99% smaller than those of the original TILDE. This efficiency is achieved by leveraging TILDE as a passage expansion model, where passages are expanded using top-k terms (e.g., top 200) to enrich their content. It provides scripts for indexing collections, re-ranking BM25 results, and training models using datasets like MS MARCO.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Academic researchers (thematic analysis), consultants (expert interviews, data rooms), policy analysts (public consultations), legal teams (discovery), market research, software engineers
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Audience
Academic researchers and developers searching for a tool to implement efficient and scalable passage re-ranking and expansion techniques
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Pricing
$0
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationSkimle
Founded: 2025
Finland
www.skimle.com
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Company Informationielab
United States
github.com/ielab/TILDE/tree/main
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Categories |
Categories |
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Qualitative Data Analysis Features
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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