Kellar

Your data,

Build AI-driven models of your own data and generate limitless amount of fully realistic synthetic data, tuned just for your own specific use case. Build, host and use your models with simple cloud-based UI and API.

We are moving towards beta testing. Subscribe to our mailing list if you want to get involved.

PRICEEACHYEAR_IDADDRESSLINE1POSTALCODECOUNTRY
95.72003897 Long Airport Avenue10022USA
81.35200359 rue de l'Abbaye51100France
94.74200327 rue du Colonel Pierre Avia75508France
83.26200378934 Hillside Dr.90003USA
10020037734 Strong St.USA
96.6620039408 Furth Circle94217USA
86.132003184, chausse de Tournai59000France
1002003Drammen 121, PR 744 SentrumN 5804Norway
98.5720035557 North Pendale StreetUSA
100200425, rue Lauriston75016France
1002004636 St Kilda Road3004Australia
10020042678 Kingston Rd.10022USA
10020047476 Moss Rd.94019USA
100200425593 South Bay Ln.97562USA
92.83200467, rue des Cinquante Otages44000France
100200439323 Spinnaker Dr.51247USA
1002004Keskuskatu 4521240Finland
1002004Erling Skakkes gate 784110Norway
94.7420047586 Pompton St.70267USA
1002004897 Long Airport Avenue10022USA

Solving data scarcity

In the era of Big data, controversially, data can feel like a scarce resource. Limited amount of relevant data can dramatically slow your application development, require you to do expensive data collection, or make your machine learning model dumber than it should be.

Efficent Application development

Modern web applications are built on top of real-world data. Without enought realistic data, your development mockups and prototypes do not communicate the right message to your test users, and understanding the value you are trying to provide may become unclear.

Comprehensive Testing

Building reliable software requires rigorious testing, and your tests require lot of data to cover enough corner-cases. Simple API-based generation of realistic test data fits well into your current CI/CD pipeline.

Smarter data-science

Most of the successfull data-science models are data-hungry, and collecting enough data might be possible only for large tech giants. With intelligent data synthetization, you can achieve large-scale representative dataset without expensive data collection.