Best Qualitative Data Analysis Software
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Compare the Top Qualitative Data Analysis Software as of June 2025
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What is Qualitative Data Analysis Software?
Qualitative data analysis software helps researchers and analysts organize, interpret, and draw insights from non-numerical data such as interviews, text, images, and audio recordings. These tools enable users to categorize and code data, identify patterns, and track themes across datasets, making it easier to handle large amounts of qualitative information. Features often include data visualization, text search, and annotation capabilities, allowing for more structured and efficient analysis. By automating certain aspects of the analysis process, qualitative data analysis software improves accuracy and speeds up research workflows. Overall, this software is essential for researchers looking to analyze complex, narrative-rich data in areas like social sciences, market research, and healthcare. Compare and read user reviews of the best Qualitative Data Analysis software currently available using the table below. This list is updated regularly.
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Get insightful text analysis with machine learning that extracts, analyzes, and stores text. Train high-quality machine learning custom models without a single line of code with AutoML. Apply natural language understanding (NLU) to apps with Natural Language API. Use entity analysis to find and label fields within a document, including emails, chat, and social media, and then sentiment analysis to understand customer opinions to find actionable product and UX insights. Natural Language with speech-to-text API extracts insights from audio. Vision API adds optical character recognition (OCR) for scanned docs. Translation API understands sentiments in multiple languages. Use custom entity extraction to identify domain-specific entities within documents, many of which don’t appear in standard language models, without having to spend time or money on manual analysis. Train your own high-quality machine learning custom models to classify, extract, and detect sentiment.
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Visual Layer
Visual Layer
Visual Layer is a platform for working with large volumes of image and video data. It supports visual search, filtering, tagging, and dataset structuring across raw files, metadata, and labels. No code is required, and both technical and non-technical teams use it in production. Common applications include curating datasets for machine learning, auditing visual content for compliance, reviewing surveillance material, and preparing media for downstream platforms. The platform detects duplicates, mislabeled items, outliers, and low-quality files to improve data quality before model training or operational decision-making. It is model-agnostic, supports both cloud and on-premise deployment, and is built by the creators of Fastdup, the widely used open-source tool for visual deduplication.Starting Price: $200/month -
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Restructured
Kolena
Restructured is an AI-powered platform designed to help businesses extract insights from unstructured data at scale. Whether dealing with documents, images, audio, or video, it combines LLM capabilities with advanced search and retrieval methods to not only index information but also understand it in context. Restructured transforms massive datasets into actionable insights, making complex data easy to navigate and analyze.Starting Price: $99/user/month
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