Synthetic Data
for Pilots, Hackathons and Innovation
Fast prototyping and hypothesis validation for Pilots, Hackathons and Innovation
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Core Value Proposition
Deliver software solutions easier, faster, and with higher quality with representative
synthetic test data
Improve the process from ideation to production
Streamline the journey from concept to deployment with seamless access to synthetic data.
Cost-effective alternative to real data
Reduce costs by using synthetic data that replicates real data without the associated expenses.
Data diversity by accessing whole datasets
Enhance innovation with diverse, comprehensive datasets that synthetic data provides.
Speed up innovation projects
Accelerate innovation by eliminating delays in data access and privacy concerns.
Faster validation of solution providers
Quickly test and validate solutions with realistic synthetic data that enhances accuracy and compliance.
Challenges when doing Pilots, Hackathons and Innovation
Innovation projects face delays and high costs due to limited access to diverse, real-world data.
Data availability
for RnD projects
- No data availability for pilot projects
- Limited data understanding leads to incorrect decisions in the analysis
- Complexity of data sharing internally and externally
Proof of business use case
- It is difficult to evaluate new solutions with real data
- It’s difficult to prove a business use case without understanding the data, yet to access the data, you must first demonstrate the business use case
Data scarcity
- Many constraints on the data available for training AI models
- Data partly not available due to privacy risks
Our solution: Test Data Management
Quality assurance
report
Assess generated synthetic data on accuracy, privacy, and speed
Syntho’s quality assurance report assesses generated synthetic data and demonstrates the accuracy, privacy, and speed of the synthetic data compared to the original data.
External evaluation
by SAS
Our synthetic data is assessed and approved by the data experts of SAS
Synthetic data generated by Syntho is assessed, validated and approved from an external and objective point of view by the data experts of SAS.
Time Series Data
Synthesize time-series data accurately with Syntho
Time series data is a datatype characterized by a sequence of events, observations and/or measurements collected and ordered with date-time intervals, typically representing changes in a variable over time, and is supported by Syntho.
Save your synthetic data guide now
What is synthetic data?
How does it work?
Why do organizations use it?
How to start?
What makes Syntho’s approach unique?
Fast Prototyping with Synthetic Data
- Allow vendors, your team, developers and data scientists to quickly access synthetic datasets, which are as good as real
- Significantly shortens the RnD cycle
Hypothesis validation before making a data access request
- Before requesting access to sensitive or proprietary datasets, one can use synthetic data to validate their hypotheses and prove the business use case before data access
High-quality data = high quality innovation
- By ensuring full data access, organizations can improve how they execute Pilots, Hackathons and Innovation, resulting in better and more innovation
