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InVariants (Beta)
Explore your data's shape with TDA, ML & AI — no code
InVariants is a no-code data platform that combines Topological Data Analysis, Machine Learning, and dimensionality reduction — and lets you export trained models as ready-to-run Python bundles. Run persistent homology, Mapper graphs, clustering, anomaly detection, time series analysis, and ML training. We're looking for beta testers. Try it free at invariants.tech.
We built InVariants to address a gap we kept encountering in data analysis workflows: standard statistical methods and classical ML describe what is in the data, but struggle to capture the underlying structural patterns — especially in high-dimensional, noisy, or topologically complex datasets.
Topological Data Analysis (TDA) was the answer, but it has historically required significant mathematical background and custom engineering to apply in practice. InVariants brings TDA into a no-code workspace alongside ML training, dimensionality reduction, anomaly detection, and time series analysis — so practitioners can explore data structure without writing a single line of code.
Key capabilities in the current beta:
• Persistent homology and Mapper graphs with AI-powered interpretation
• ML training with SHAP explainability, PDP/ICE plots, and model export as a self-contained Python bundle
• Anomaly detection, ARIMA forecasting, and rolling TDA for time series
• Full data preparation pipeline with undo history
We are actively looking for beta participants — particularly data scientists, analysts, and ML engineers working with complex or high-dimensional data. Access is free during the beta period.
Apply at invariants.tech — happy to answer questions here.
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About InVariants (Beta) on Product Hunt
“Explore your data's shape with TDA, ML & AI — no code”
InVariants (Beta) was submitted on Product Hunt and earned 4 upvotes and 1 comments, placing #160 on the daily leaderboard. InVariants is a no-code data platform that combines Topological Data Analysis, Machine Learning, and dimensionality reduction — and lets you export trained models as ready-to-run Python bundles. Run persistent homology, Mapper graphs, clustering, anomaly detection, time series analysis, and ML training. We're looking for beta testers. Try it free at invariants.tech.
InVariants (Beta) was featured in Analytics (172.3k followers), Artificial Intelligence (471k followers) and Data Science (3.8k followers) on Product Hunt. Together, these topics include over 115.6k products, making this a competitive space to launch in.
Who hunted InVariants (Beta)?
InVariants (Beta) was hunted by Angel Ramos. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Angel Ramos