Need test data? Smarter synthetic data is better than production data

Say goodbye to low-value work and focus on high-performing testing and driving efficient software development

How does MOSTLY AI help CTOs, team leads, QAs, and developers improve software development and testing?

Realistic AI-generated test data at scale
Sensitive data anonymizationon
Safe data-sharing
Efficient application building

Customers who already use synthetic data

MOSTLY AI's synthetic data generator is trusted by major industry players across different sectors
Sign up and generate high-quality test data for free
It takes just a few clicks to turn your production data into smarter synthetic test data.

Why is production and mock data not sufficient for testing anymore?

Beware of legacy data anonymization and generation techniques as they destroy the utility of data, kill your team’s efficiency, and endanger data privacy. Be smart and generate smarter synthetic data for speed, velocity, flexibility and cost-reduction.

Production data

Should not be used without proper anonymization
It‘s almost impossible to properly anonymize
Lacks outliers needed for negative testing
Too big and cumbersome to manage
Too small for stress tests

Rule-based mock data

70% of all test data is still created manually
Impossible to recreate all relevant business rules
Needs expert domain knowledge regarding the data
Not easy to maintain referential integrity
No correlations, no meaningful data

Why smarter synthetic data for testing?

0x
faster to generate
up to
0%
decrease in testers' time utilization

0%
compliant with the strictest legislation

The smarter way
to test software

Not only can you get test data faster than the competition, you get a whole load of other benefits.
Sign up for free
Automate the process of generating high quality test data – the MOSTLY AI platform does the heavy lifting for you
No need to manually configure business rules anymore – you do not even need to know the details of the data you are working with
Do not worry about protecting privacy – in-built privacy guarantees will result in 100% anonymous test data
Cover more test cases with rich synthetic data – better test coverage means fewer bugs and higher reliability for your software
Create as much data as you need – perform load and performance tests at ease

How does MOSTLY AI’s synthetic data platform work?

1

Connect your source database

2

Define the tables where you want to protect individuals’ privacy

3

Start the synthetization - the platform automatically learns your data structures and business rules

4

Save the synthetic data to your target database

What databases and cloud buckets does MOSTLY AI support?

Direct database access

Direct cloud bucket access

Supporting various data types

  • Numerical, categorical
  • Datetime
  • Geolocation
  • Character Sequences
  • Text

Secure deployment options

Either deploy in our cloud infrastructure or your environment (on-prem or in your private cloud)

User management

And much more

  • Easy to use, self-service UI
  • REST API
  • Mock data generation
  • Data Catalog for automation

Unparalled synthetic data quality

3-10x better than any competitor
Try for free

Why testers and developers use MOSTLY AI’s synthetic data?

Sign up for free
MOSTLY AI’ platform helps you to:
Get AI-generated data at scale representative of the whole production data in just minutes
Deidentify data
Subset your entire data into smaller, more managable, yet representative batches 
Speed up sprints and agility
Create bigger and more robust data from smaller sets for performance and load testing
Automate data generation using the Data Catalog function
Reduce costs of data generation
Comply with the stringest legislation. Our data is GDRP and CCPA-ready.
  • "Partnering with MOSTLY AI allowed us to experiment with Synthetic Data. We have recognized the potential values of this approach very early on, and found out the best partner in this field. We believe Synthetic Data is one of the best ways  to build powerful data-driven banking experiences, without compromising on customer privacy and being fully compliant with GDPR."
    Erste Group Research and Digital Development
    George Labs GmbH
  • “Working with synthetic data, we can develop and test our services in a much more sophisticated manner than before, while still ensuring complete privacy protection for our customers.”
    Maurizio Poletto
    Chief Platform Officer, ERSTE Group
  • "On our way to be the digitalization capital, we actively shape the digital transformation. Through cooperation with companies such as MOSTLY AI, we take an important step to enable data-driven innovation by providing even more valuable Open Data while ensuring full anonymization of personal information through data synthetization."
    Brigitte Lutz
    Data Governance Coordinator, City of Vienna
  • "MOSTLY AI has demonstrated quickly how innovative approaches can benefit a group like Telefónica. This makes it all the more exciting that the start-up will help wayra to make the cooperation of other start-ups in our hub with Telefónica even smoother and more effective in the future."
    Florian Bogenschütz
    Managing Director, wayra, TELEFONICA
  • "As a financial investor and a close partner to MOSTLY AI, we are strongly convinced that MOSTLY AI will fundamentally revolutionize the analysis and usage of large data sets. Their Synthetic Data Platform unlocks big data assets while at the same time guaranteeing the highest levels of data protection. That helps customers securely train predictive models and thereby unleashing the full potential of their data."
    Christian Nagel
    Managing Partner, EARLYBIRD
  • “We see synthetic data as the foundation for all future data-driven development, as it provides the only GDPR-compliant method for unlocking advanced analytics and insights based on customer data."
    Dietmar Böckmann
    Managing Director, s IT Solutions, ERSTE Group
Sign up and generate high-quality test data for free
It takes just a few clicks to turn your production data into smarter synthetic test data.

Request a demo - no pitch slapping, no buzz words. All your questions answered.

Meet our team. Always happy to listen, consult and answer your questions. Get all your synthetic data questions answered.

Certifications

Compliant with

Questions & answers

Both options are available. Please check our plans here
Production data needs proper anonymization and proper anonymization of production data is near-impossible. Behavioral data especially.

Rule-based mock data is hard to create and mock data requires expert knowledge of the data. Mock data has no correlations and referential integrity is hard to maintain.

With MOSTLY AI’s platform you can automate data anonymzation without any expertise in the data that you want to synthesize. You get high-quality test data with preserved referential integrity in minutes.
Generative AI mimics data so well that you can end up with a 1:1-like connection to your original data. The important underlying concept of synthetic data is that there are no 1:1 relationships between the original and the synthetic data. The real data is only used as learning material during the synthesization process. Only generalizable patterns, distributions or correlations are learned. MOSTLY AI’s platform generates synthetic data from scratch based on these patterns. There is no 1-to-1 link between original and synthetic data. Because of this missing 1-to-1 link, there is no direct attack surface for re-identifying sensitive information.

However, it is essential to point out that not all synthetic data is created equal. There are open source solutions out there without additional privacy mechanisms in place that can leak privacy. The process of synthesization does not guarantee privacy in itself. One of the possible issues is outliers or extreme values that can easily be re-identified.

MOSTLY AI’s platform uses different mechanisms to safeguard against privacy and re-identification risks. The first mechanism makes sure that our deep learning algorithm will not overfit the original data. The second mechanism is built-in privacy protections on all levels. We automatically disable all categories used by a few sets of individuals and protect extreme values in other data types as there could be a privacy risk. The third mechanism is the quality assurance report after generation. We evaluate the model and each batch of generated synthetic data with strict privacy metrics to detect any and all privacy risks.

Yes, MOSTLY AI’s platform can synthesize entire databases. You can have different tables and multiple connections between tables. MOSTLY AI supports numerous tables, and it can synthesize complete data sets.

The difference is in the basic approach. MOSTLY AI generates an entirely new data set that leaves no room for re-identification. The problem with data masking is that there is still a risk of re-identification. There is no good tradeoff between data masking and data utility. The approach we use is more secure, and it also opens the door to what we call programmable synthetic data. You can instruct the generative AI to generate data as you want.

We believe that synthetic data is not just about privacy. We believe that generative AI can improve businesses by unlocking the value in data for the problems that companies are trying to solve. For that reason, our next step is to work on programmable data.

We have both. We have a UI to test and validate everything from the customers' perspective. And you can orchestrate synthesization jobs through MOSTLY AI’s APIs.

Many customers are generating data to train and improve their ML and AI models. Generative AI-powered synthetic data can provide different advantages to AI/ML models, improve their performance and preserve the privacy of the original data.

There is no golden rule for that. It depends on the patterns, hidden business rules, and what you try to replicate. If you want to do text synthesization, generative AI will need more samples than categorical data. You can start with as little as 5000 rows, but you can leverage as much data as you want to upload. There is no limit. You can also get synthetic data from just a sample from your production data.


From a quality perspective, synthetic data looks real. MOSTLY AI’s platform provides a detailed QA report from a quality assurance perspective. We check the adherence of the synthetic data to the original data in terms of data distribution.

And the quality is not limited to the distribution adherence of single columns - what we call the univariate distribution. Our generative AI model can ensure a high quality of any column combination. Bi-variate, tri-variate, and so on.



The price is less than you think. We recommend that you first sign up for our free version and get to know MOSTLY AI’s platform completely free of charge. If you enjoy the platform, contact our friendly sales team and get all your questions answered.



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