Top 10 Synthetic Data StartupsMaking a Mark in the Tech Sphere
Synthetic data provides the developers with the flexibility of scalability and freedom from biases.
Designing good data-driven models hugely depends on the quality of data. Well, data is a set of numbers, and shouldn’t bother the developers much. As they say, the devil lies in the details, real data comes with a set of issues like imbalanced classes, inherent biases, unstructured values, etc. On the other hand, synthetic data provides the developers with the flexibility of scalability of data and freedom from biases, opening a whole lot of possibilities for creating a model that doesn’t exist in the real world. In addition, synthetic data holds the benefits of protecting user data privacy all while giving the freedom to experiment with. The synthetic data market though nascent is slowly and gradually developing and will occupy at least 60% of the data used to develop AI and analytics projects by 2024 (Gartner). Given the increasing regulatory norms being imposed on access to public data, it becomes imperative that companies look for alternative sources. Here we present you with the top 10 synthetic data companies which are not only leveraging this gap but are doing quite well in making a difference in AI model development.
A synthetic data engine service companies can leverage to generate synthetic data for their realistic and representative data needs. Powered with deep learning algorithms, it can generate data at scale that is quite efficient at learning patterns, structure and variation from existing data. The engine comes with an in-built privacy mechanism to ensure the valuable information is protected, making re-identification of the individual impossible.
Location: United Kingdom
Named as 2021 Gartner Cool Vendor in AI Governance and responsible AI, Hazy gained popularity for delivering synthetic data that preserves fine-grained signals. It basically serves financial companies and has gained popularity for its data generation services which can fix class imbalances, which is the main hurdle in financial data modeling. They boast of generative algorithms trained with differential data privacy to generate data free of real customer information.
A leading synthetic data company, known for its high-quality data, operates in areas that have high-stakes use cases for artificial intelligence and sample islands that potentially have hurdles in high-quality predictive modeling.Synthetiac is a synthetic data engine that works for image processing and identification. Its rapid automatic image categorization technology can accurately identify objects in question, including the rare ones.
Specialized in generating data for models based on computer vision model development, it has emerged as a pioneer in developing more capable and ethical AI models. It is a venture-backed startup leveraging CGI and deep learning to help companies develop models in no time and at cost of human-annotation models.
Datomize specializes in generating synthetic data on the lines of an organization’s existing data, to enable data to have an element of mimicking for the developed models to sound authentic. It generates the synthetic data through advanced AI and machine learning technologies to generate personal data, which offers compliance with most of the privacy regulations
As an open-source data-as-code tool, it provides a simple CLI workflow for generating data that is correct, anonymized, and looks like the original data. This data-generating engine is database agnostic and tests against real-life data in no time. Using data as code is a unique feature with a synth that helps generate thousands of semantic types such as credit card numbers, email addresses, and more.
Location: United Kingdom
An advanced Data Science technology and research company SkyengineAI has also advanced into synthetic data generation. Its synthetic data generation solutions are primarily aimed at improving AI and computer vision models. It is one of the world’s leading full-stack deep learning and synthetic data-generating platforms for data scientists to accelerate model development at scale. It was founded as a research and scientific spin-off in London, UK and they call themselves a fuel refinery for synthetic data.
An artificial intelligence service provider specializes in generating sensitive data for companies to conduct research without having to violate sensitive data. Their unique solutions for utilizing the structure of original data and the metrics which guarantee integrity and security of original data are well appreciated in the AI industry.
A platform as a service for creating synthetic data, it enables companies in overcoming challenges in acquiring and using real-world data. The data helps the developers to experiment with sensor models, scene content, and post-processing imagery effects, characterizing and cataloging both existing and synthetic datasets. Easily movable data to cloud repositories enables easy processing and training.
Specialized in designing fraud detection models that are based on insights, their synthetic fraud scores are known for precision and best-in-class false positive rates to help accurately identify synthetic fraud. SentiLink’seCBSV product verifies SSNs directly with the social security administration in real-time