Equip yourself with the most comprehensive synthetic data platform on the market
MOSTLY AI 2.1 continues our mission to deliver an enterprise-grade synthetic data platform and remain the leader in the tabular synthetic data space.
We now support the DB2 family of databases, enabling synthetic data for mainframe applications.
Our new Text encoding type allows you to synthesize unstructured natural language. MOSTLY AI 2.1 now covers all tabular data types, from categories to geolocation data and beyond. The world is all yours!
Benefit from searchable and interactive charts in the QA report, allowing you to intuitively spot opportunities to further improve synthetic data quality.
Put unstructured natural language texts to use in your AI/ML applications.
Insurance claim reports, medical diagnoses, and other types of unstructured texts are very rich sources of information, capturing details that aren’t present in numbers or other structured forms of data.
Our new Text encoding type allows you to privacy-protect these texts and put them to use in various AI/ML use cases, for example:
Testing—by generating real descriptions
E-commerce analytics—by synthesizing customers' search keywords
Use DB2 databases for synthetic data
You can now connect MOSTLY AI to the DB2 family of databases.
Use them as a data source or as a destination, and enable synthetic data for mainframe applications.
All privacy and accuracy charts are now in a hand’s reach
Our privacy and accuracy charts are now available in the web UI, so you can intuitively evaluate the quality of your synthetic data.
Spot opportunities to further improve quality and immediately apply them to the job settings.
Use the search function to look up specific columns.
Interactive charts allow you to learn more about specific data points.
Enlarge them to study them in detail.
Job cancellation hangs when using AWS ECR.
Job won’t start if the
Jobs may crash if they process very wide tables.
AI model training crashes when consistency correction and GPU acceleration are both active.
Synthetize your data wherever it is
Mostly AI 2.0 is now capable of synthesizing entire databases!
It connects to your data sources, recognizes its columns and their relationships, and provides you with a synthetic version of your data wherever you need it.
There are no more limits to what you can synthesize. Connect to your databases, buckets, and files without any hurdles.
Be ready for the synthetic data revolution. It’s already here.
A new customer centric UI
With Mostly AI 2.0 we introduce a new UI!
The new UI has been redesigned with a customer centric approach.
The task of creating a new synthesization job has never been easier.
And it looks cool too!
Synthesize complex data structures
With Mostly AI 2.0 it is now possible to define multi-table data catalogs!
The complexity of your data source is now represented in the data catalog:
Support of primary keys,
Support of foreign keys,
and Referential integrity.
The platform understands the relationships between all the tables and create a synthesization plan based on these relationships.
The result is synthetic version of your data in its original form!
Better performance thanks to parallelization
Thanks to a major architectural redesign, the Mostly AI platform now supports parallel computing.
In case of multi-table synthetic generation, the Mostly AI platform will intelligently divide the tasks that can be calculated in parallel in the available VMs.
Create your data source once and re-use it!
You can now define data connectors in the Mostly AI platform!
Data connector can be used as a source of data or as a data destination.
You can fetch data from your production data lake or database and push them wherever you need!
A perfect way to test the extremes
Some of the biggest challenges when testing software can be getting the software into some very specific states. You want to test that the new error message works, but this message is only shown when something breaks. You may have no direct control over and you really need to manipulate this data in order to perform your tests.
You can now define Mock Data in the generation process!
Mock data makes it possible to simulate errors and circumstances that would otherwise be very difficult to create in a real world environment.