Global Startup Heat Map highlights 10 Synthetic Data Startups to Watch in 2023
Through the Big Data & Artificial Intelligence (AI)-powered StartUs Insights Discovery Platform, which covers over 3 790 000+ startups & scaleups globally, we identified 1034 synthetic data startups. The Global Startup Heat Map below highlights the 10 synthetic data startups you should watch in 2023 as well as the geo-distribution of all 1034 startups & scaleups we analyzed for this research. Based on the heat map, we see high startup activity in the US and Western Europe, followed by India. These synthetic data startups work on solutions ranging from computer vision models to data augmentation and bias mitigation to text-to-video generation.
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As the world’s largest resource for data on emerging companies, the SaaS platform enables you to identify relevant technologies and industry trends quickly & exhaustively. Based on the data from the platform, the Top 5 Synthetic Data Startup Hubs are in London, New York City, San Francisco, Bangalore & Mumbai. The 10 hand-picked startups highlighted in this report are chosen from all over the world and develop solutions for data generation, synthetic patient records, personalization, and robotic intelligence.
10 Top Synthetic Data Startups to Watch in 2023
Innovations in synthetic data open up possibilities for data analysis, privacy protection, and machine learning. Synthetic data refers to artificially generated data that mimics the statistical characteristics of real data while preserving privacy and confidentiality. Recent advances in this field lead to the development of sophisticated algorithms and techniques that create realistic and representative synthetic datasets. By leveraging generative adversarial networks (GANs) and differential privacy, synthetic data is generated with minimal risk of re-identification. This enables organizations to share and analyze sensitive data without compromising individual privacy. Moreover, synthetic data serves as a valuable resource for training machine learning models in situations where acquiring or labeling real data is costly or impractical. The use of synthetic data promotes innovation, ethical data practices, and AI model development while addressing privacy concerns and data scarcity.
- SBX Robotics – Synthetic Data On-demand
- AGICortex – Robotic Intelligence
- Dedomena – Structured Data Generation
- Synthetic Media Processing Laboratory – Audio Processing
- Kroop AI – Personalized Videos
- BlueGen – Data Augmentation
- Colossyan – Text-to-Video Generation
- Synthetic Images – Computer-Generated Imagery (CGI) Generation
- Fairgen – Algorithmic Bias Mitigation
- MediSyn – Synthetic Patient Records
SBX Robotics provides Synthetic Data On-demand
Canadian startup SBX Robotics develops a synthetic data generation platform to offer datasets for training computer vision models. The startup’s platform takes a small set of representative real-world data (RWD) to generate realistic and annotated large training data repositories. It benchmarks the generated dataset against RWD through iterative testing and optimizations as well as provides rapid iteration support for dataset updates. Its synthetic data trains vision models for object detection, segmentation, keypoint detection, and 6D pose estimation models. This streamlines the robot training process and improves automation in many industries. They include warehousing, logistics, food processing, agriculture, construction, manufacturing, and automobile.
AGICortex advances Robotic Intelligence
Polish startup AGICortex builds agicframework, a multi-modal machine learning (ML) tool for robotic automation. It provides pre-trained AL models for different machine intelligence requirements leveraging synthetic and real data. The tool features automatic data collection and real-time learning that collects data during operation and provides a filtered database with a high signal-to-noise ratio. This enables its AI models to adapt to the changing physical world and eliminate the need for a training phase. Its pre-trained models also facilitate environment understanding, autonomous learning, and spatial awareness as well as offer analytics and explainable AI to eliminate post-processing. Further, the startup’s low-code developer application programming interfaces (APIs) support integration with robotic operating systems (ROS). AGICortex’s solution equips robots, drones, and other machines with AI-based autonomous general intelligence and accelerates automation.
Dedomena enables Structured Data Generation
Spanish startup Dedomena develops a synthetic data generation platform. It utilizes RWD to create synthetic data that replicates the statistical, informational, and predictive components of RWD. The platform learns and analyzes the input real data patterns to recommend and configure the synthesization task and AI model training. Further, it provides a quality assurance (QA) report to evaluate the utility and privacy of the generated data. The platform also integrates the generated data directly into existing data pipelines, processes, and environments and employs mathematical methods to ensure privacy compliance. This aids structured and unstructured synthetic data for training AI models in industries such as banking, insurance, mobility, and healthcare.
Synthetic Media Processing Laboratory advances Audio Processing
Singaporean startup Synthetic Media Processing Laboratory makes ML and deep learning-based audio processing software. The startup’s solution leverages deep neural networks for digital signal processing to improve online audio as per network, devices, and acoustic environments. It thus offers efficient codecs, echo cancellation, background noise reduction, packet loss concealment, and device audio management in online environments. The startup’s software enhances the audio and conversations for businesses and individuals working and learning online.
Kroop AI provides Personalized Videos
Indian startup Kroop AI develops The Artiste Studio, an ethical AI data platform for creating synthetic audio-visual content. It features high-quality text-to-video generation and content localization through lip-syncing. The platform also creates personalized chat assistants with facial animation. It utilizes natural language processing (NLP) as input to generate personalized video content in any language, voice, or avatar. As a result, it automates studio-like quality personalized video content synthesis for businesses in advertising, healthcare, sports, telecommunications, and banking among others.
BlueGen facilitates Data Augmentation
Dutch startup BlueGen creates a cloud and on-premise platform for privacy-complaint data synthesis and augmentation. The startup’s platform leverages AI and a differential privacy system to learn and synthesize data that mimics the behavior of real data. It ingests real tabular data to produce dummy data with the same statistical distribution, business rules, and referential integrity. Further, its AI utilizes existing data as a reference to augment datasets, create edge cases, complement incomplete datasets, or generate data subsets. The platform enables multi-user federated data generation at scale without exposing the real data or user identity. Data engineers and QA professionals use this platform to generate training data for ML models and accelerate continuous software development and testing.
Colossyan enables Text-to-Video Generation
UK-based startup Colossyan builds Colossyan Creator, an AI-based platform for realistic synthetic video creation using text-to-video generation. The startup’s AI algorithms enable video creation and editing from inputs such as texts, PDFs, reports, PowerPoint, speech, or text command prompts. It provides customized AI actors to present the videos with required emotions and expressions in multiple supported languages. The startup enables non-professionals to create and edit personalized videos and brand content for education, training, marketing, and sales at low costs. It enables corporate users to convert PPTs and PDFs into engaging videos for corporate communications and product or service explainer videos. Similarly, content creators use Colossyan Creator to create scenario-based videos with multiple actors and save time and cost.
Synthetic Images advances CGI Generation
German startup Synthetic Images offers on-demand, photorealistic synthetic image data, and label datasets to train computer vision models. The startup combines deep learning models, generative adversarial networks (GANs), CGI, and visual effects (VFX) for labeled image generation. It also leverages use-case descriptions, 3D files, and reference images of the objects or scenes of interest as input parameters. This way, it offers diverse image datasets with multiple permutations of plausible values, representing scene variations. The startup’s solution also includes random distractors to evade overfitting. This improves computer and machine vision models for applications in defect detection, assembly inspection, and pose estimation. Consequently, the solution improves the performance of automated visual inspection and vision-guided robots, finding use in the automotive, healthcare, and manufacturing industries.
Fairgen facilitates Algorithmic Bias Mitigation
Israeli startup Fairgen offers debiasing-as-a-service through its software platform and APIs. The AI-powered platform takes sample customer surveys and augments them by generating bias-free synthetic survey responses. This way, the platform rectifies inherent algorithmic biases in existing datasets and produces niche demographic insights for ML model training. The platform is industry agnostic and reduces the time and cost of discrimination-free data collection.
MediSyn generates Synthetic Patient Records
US-based startup MediSyn enables structured and longitudinal synthetic patient EHR generation using ML and large language models (LLMs). The platform runs realistic simulations on electronic health records (EHRs) using its customized ML generator and produces high-fidelity and high-dimensional patient database and medication data. Additionally, it enables targeted patient record generation for specific health conditions as well as medical codes for diagnosis and procedures. This synthetic generator equips healthcare researchers with realistic longitudinal patient records to accelerate research without comprising data quality and patient privacy.
Discover All Emerging Synthetic Data Startups
The 10 synthetic data startups showcased in this report are only a small sample of all startups we identified through our data-driven startup scouting approach. Download our free Industry Innovation Reports for a broad overview of the industry or get in touch for quick & exhaustive research on the latest technologies & emerging solutions that will impact your company in 2023!
