Build better products with the right third-party data
Leverage 1,000s of attributes about people, companies, properties, and more to augment the impact of your internal data
Using ROI-positive external data in production was never so easy
Discover
Sign up for free and explore our catalog that contains dozens of curated options of data vendors and APIs. Quickly access critical information such as match and fill rates, response time, inputs, output, and more.
Evaluate
Find the real value of dozens of vendors by using our automated evaluation framework. Uncover match rates, fill rates, and correlations for the each attribute provided by different APIs and estimate the lift on your models.
Deploy
Use the Tint API to access normalized data from the multiple vendors with a single call and securely store your data in our data warehouse. Ship products much faster and monitor them in production. Your developers will love you.
Superpowers for you, on us
Performance
Tap into thousands of external attributes to achieve your product goals
Speed to market
Use Tint's data infrastructure to reduce development time that slows your progress
Magical easy of use
Discover and evaluate new relevant data sources effortlessly
Flexibility
A/B test vendors in production and switch data sources easily without writing code
ROI
Improve the accuracy of your decisions while balancing data costs
Secure and Private
We keep your data in our secure sandbox that is not shared with any other parties
Examples of use cases
Instant onboarding decisions
Machine learning models unlock real-time onboarding decisions and enable growth with low risk. Tint identifies external variables about users that enrich your data and improve predictive performance. For example, do users that have a prepaid phone have a higher risk? Would the predictive power increase when we cross this information with the age of the email used?
Better insurance pricing
More data about a user allows insurers to make better pricing decisions and to run a more profitable book. By using Tint, insurers quickly identify external data that helps them refine their models and grow with profitable revenue. For example, are the housing characteristics provided during the quote accurate? Does employment information affect the probability of a claim?
Better credit decisions
Financial institutions rely on imperfect data like credit score, that may exclude millions of customers, to make lending decisions. By using Tint, lenders can identify signals that would complement, or even replace, credit scores. For example, could employment and education information help predict the risk of uses with thin file? How about income information? Are there signals that can replace credit data with a better ROI?