ROI-positive data from external vendors is just a few clicks away

Tint Augment® uses AI-powered technology to significantly reduce time and cost required to discover and to evaluate thousands of variables from third-party vendors in context.

Dataset upload

You upload dataset in .csv format (only step required from you)


Data augmentation augments your dataset with data from a curated list of partners and measure value using machine learning techniques


Smart evaluation for your problem reports the ROI of each variable based on your specific use case

Superpowers for you, hassle-free



Improve the accuracy of your decisions while balancing data costs


Holistic evaluation

Capture interaction effects between features in context.


Magical easy of use

Discover and evaluate new relevant data sources effortlessly.



Bank grade security in all data exchanges.



Your dataset is kept in a sandbox environment and is not shared with other parties. All data is deleted after test is over.


Privacy and GDPR ready

The processes are fully compliant with GDPR requirements.

Measure the impact of external data on your problems

Online marketplaces

Improve accuracy of onboarding models

Machine learning models unlock real-time onboarding decisions and enable growth with low risk. identifies external variables about users that enrich the training set and improve predictive performance. For example, do users that have a prepaid phone have higher risk? Would the predictive power increase when this information is crossed with the age of the email used?


Underwrite smarter risks

More data about a user improves underwriting and increases profitability. By using, insurers quickly identify external data that helps them refine their models and grow with profitable revenue. For example, do weather and traffic information impact the risk of a car accident? How to go beyond zipcode? Or does employment information affect the probability of a claim?


Reach customers beyond credit scores

Financial institutions rely on imperfect data like credit score, which exclude millions of customers, to make lending decisions. By using, lenders can identify signals that complement, or even replace, credit scores. For example, can employment and education information help predict the risk of users with thin file? Are there other signals that can provide better ROI than credit scores?

Sign up for the beta

Discover ROI-positive data from hundreds of external sources in a few clicks and build better predictive models for risk.