Data PipelinesUpgini
Automated data & feature enrichment for machine learning
- Status
- Generally available
- Last checked
- Aging · Sep 5, 2026
- License
- Open source
- Pricing
- Free tier · from $0
What it is
Upgini is a free automated library that enriches your training dataset with accuracy-improving features from public and community-shared sources, enhancing the performance of machine learning models.
Upgini stands out by automating the search and integration of accuracy-improving features from a wide range of public and community-shared datasets, making it easier for developers to enhance their machine learning models.
When it fits — and when it doesn’t
A good fit for
Projects where manual feature engineering is time-consuming or impractical
Developers looking to quickly improve model accuracy without extensive data preparation
Research teams needing to explore a wide range of features for their models
Look elsewhere if
Real-time applications requiring immediate feature updates
Scenarios with strict privacy requirements where public data sources cannot be used
Known weaknesses
Each one links to the public issue, changelog or docs page it came from, where we have one.
- 01
Limited integrations with non-Python data ecosystems
Primary support for Python libraries and frameworks, limited direct integration with R or Julia environments
- 02
Small community contribution to feature sources
Community-shared datasets are sparse compared to public data availability
What it does well
Automated feature enrichment from public and community data sources
Improves model accuracy by integrating relevant features
Open-source with BSD-3-Clause license
Pricing
- Free tier
- YesOpen source — free to use
- Paid from
- $0
- Model
- Flat rate
- Enterprise plan
- No
Pricing not independently confirmed — check the vendor’s page.
Performance benchmarks
How Fast Is It?
Set up Upgini
Setup steps, common gotchas and what to check after 30 days.