Alternatives to DataGen
Compare DataGen alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to DataGen in 2026. Compare features, ratings, user reviews, pricing, and more from DataGen competitors and alternatives in order to make an informed decision for your business.
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OORT DataHub
OORT DataHub
Data Collection and Labeling for AI Innovation. Transform your AI development with our decentralized platform that connects you to worldwide data contributors. We combine global crowdsourcing with blockchain verification to deliver diverse, traceable datasets. Global Network: Ensure AI models are trained on data that reflects diverse perspectives, reducing bias, and enhancing inclusivity. Distributed and Transparent: Every piece of data is timestamped for provenance stored securely stored in the OORT cloud , and verified for integrity, creating a trustless ecosystem. Ethical and Responsible AI Development: Ensure contributors retain autonomy with data ownership while making their data available for AI innovation in a transparent, fair, and secure environment Quality Assured: Human verification ensures data meets rigorous standards Access diverse data at scale. Verify data integrity. Get human-validated datasets for AI. Reduce costs while maintaining quality. Scale globally. -
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DATPROF
DATPROF
DATPROF Test Data Platform is a complete test data management solution that helps software teams create, protect, provision, and automate high-quality test data. The platform combines data masking, synthetic test data generation, data subsetting, test data provisioning, and automation in one integrated solution. DATPROF enables organizations to safely use realistic, production-like data for development, testing, QA, and CI/CD pipelines without exposing sensitive or privacy-related information. It helps companies comply with regulations such as GDPR, PCI, and HIPAA while improving software delivery speed and reducing manual test data work. DATPROF is a software company specialized in test data management. Its mission is to help organizations make test data available faster, safer, and more efficiently, especially in complex enterprise and regulated environments. -
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Scale GenAI Platform
Scale AI
Build, test, and optimize Generative AI applications that unlock the value of your data. Optimize LLM performance for your domain-specific use cases with our advanced retrieval augmented generation (RAG) pipelines, state-of-the-art test and evaluation platform, and our industry-leading ML expertise. We help deliver value from AI investments faster with better data by providing an end-to-end solution to manage the entire ML lifecycle. Combining cutting edge technology with operational excellence, we help teams develop the highest-quality datasets because better data leads to better AI. -
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Bitext
Bitext
Bitext provides multilingual, hybrid synthetic training datasets specifically designed for intent detection and LLM fine‑tuning. These datasets blend large-scale synthetic text generation with expert curation and linguistic annotation, covering lexical, syntactic, semantic, register, and stylistic variation, to enhance conversational models’ understanding, accuracy, and domain adaptation. For example, their open source customer‑support dataset features ~27,000 question–answer pairs (≈3.57 million tokens), 27 intents across 10 categories, 30 entity types, and 12 language‑generation tags, all anonymized to comply with privacy, bias, and anti‑hallucination standards. Bitext also offers vertical-specific datasets (e.g., travel, banking) and supports over 20 industries in multiple languages with more than 95% accuracy. Their hybrid approach ensures scalable, multilingual training data, privacy-compliant, bias-mitigated, and ready for seamless LLM improvement and deployment.Starting Price: Free -
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AI Verse
AI Verse
When real-life data capture is challenging, we generate diverse, fully labeled image datasets. Our procedural technology ensures the highest quality, unbiased, labeled synthetic datasets that will improve your computer vision model’s accuracy. AI Verse empowers users with full control over scene parameters, ensuring you can fine-tune the environments for unlimited image generation, giving you an edge in the competitive landscape of computer vision development. -
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Anyverse
Anyverse
A flexible and accurate synthetic data generation platform. Craft the data you need for your perception system in minutes. Design scenarios for your use case with endless variations. Generate your datasets in the cloud. Anyverse offers a scalable synthetic data software platform to design, train, validate, or fine-tune your perception system. It provides unparalleled computing power in the cloud to generate all the data you need in a fraction of the time and cost compared with other real-world data workflows. Anyverse provides a modular platform that enables efficient scene definition and dataset production. Anyverse™ Studio is a standalone graphical interface application that manages all Anyverse functions, including scenario definition, variability settings, asset behaviors, dataset settings, and inspection. Data is stored in the cloud, and the Anyverse cloud engine is responsible for final scene generation, simulation, and rendering. -
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DataCebo Synthetic Data Vault (SDV)
DataCebo
The Synthetic Data Vault (SDV) is a Python library designed to be your one-stop shop for creating tabular synthetic data. The SDV uses a variety of machine learning algorithms to learn patterns from your real data and emulate them in synthetic data. The SDV offers multiple models, ranging from classical statistical methods (GaussianCopula) to deep learning methods (CTGAN). Generate data for single tables, multiple connected tables, or sequential tables. Compare the synthetic data to the real data against a variety of measures. Diagnose problems and generate a quality report to get more insights. Control data processing to improve the quality of synthetic data, choose from different types of anonymization, and define business rules in the form of logical constraints. Use synthetic data in place of real data for added protection, or use it in addition to your real data as an enhancement. The SDV is an overall ecosystem for synthetic data models, benchmarks, and metrics.Starting Price: Free -
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Bifrost
Bifrost AI
Quickly and easily generate diverse and realistic synthetic data and high-fidelity 3D worlds to enhance model performance. Bifrost's platform is the fastest way to generate the high-quality synthetic images that you need to improve ML performance and overcome real-world data limitations. Prototype and test up to 30x faster by circumventing costly and time-consuming real-world data collection and annotation. Generate data to account for rare scenarios underrepresented in real data, resulting in more balanced datasets. Manual annotation and labeling is an error-prone, resource-intensive process. Easily and quickly generate data that is pre-labeled and pixel-perfect. Real-world data can inherit the biases of conditions under which the data was collected, and generate data to solve for these instances. -
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Symage
Symage
Symage is a synthetic data platform that generates custom, photorealistic image datasets with automated pixel-perfect labeling to support training and improving AI and computer vision models; using physics-based rendering and simulation rather than generative AI, it produces high-fidelity synthetic images that mirror real-world conditions and handle diverse scenarios, lighting, camera angles, object motion, and edge cases with controlled precision, which helps eliminate data bias, reduce manual labeling, and dramatically cut data preparation time by up to 90%. Designed to give teams the right data for model training rather than relying on limited real datasets, Symage lets users tailor environments and variables to match specific use cases, ensuring datasets are balanced, scalable, and accurately labeled at every pixel. It is built on decades of expertise in robotics, AI, machine learning, and simulation, offering a way to overcome data scarcity and boost model accuracy. -
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YData
YData
Adopting data-centric AI has never been easier with automated data quality profiling and synthetic data generation. We help data scientists to unlock data's full potential. YData Fabric empowers users to easily understand and manage data assets, synthetic data for fast data access, and pipelines for iterative and scalable flows. Better data, and more reliable models delivered at scale. Automate data profiling for simple and fast exploratory data analysis. Upload and connect to your datasets through an easily configurable interface. Generate synthetic data that mimics the statistical properties and behavior of the real data. Protect your sensitive data, augment your datasets, and improve the efficiency of your models by replacing real data or enriching it with synthetic data. Refine and improve processes with pipelines, consume the data, clean it, transform your data, and work its quality to boost machine learning models' performance. -
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TagX
TagX
TagX delivers comprehensive data and AI solutions, offering services like AI model development, generative AI, and a full data lifecycle including collection, curation, web scraping, and annotation across modalities (image, video, text, audio, 3D/LiDAR), as well as synthetic data generation and intelligent document processing. TagX's division specializes in building, fine‑tuning, deploying, and managing multimodal models (GANs, VAEs, transformers) for image, video, audio, and language tasks. It supports robust APIs for real‑time financial and employment intelligence. With GDPR, HIPAA compliance, and ISO 27001 certification, TagX serves industries from agriculture and autonomous driving to finance, logistics, healthcare, and security, delivering privacy‑aware, scalable, customizable AI datasets and models. Its end‑to‑end approach, from annotation guidelines and foundational model selection to deployment and monitoring, helps enterprises automate documentation. -
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Synetic
Synetic
Synetic AI is a platform that accelerates the creation and deployment of real-world computer vision models by automatically generating photorealistic synthetic training datasets with pixel-perfect annotations and no manual labeling required, using advanced physics-based rendering and simulation to eliminate the traditional gap between synthetic and real-world data and achieve superior model performance. Its synthetic data has been independently validated to outperform real-world datasets by an average of 34% in generalization and recall, covering unlimited variations like lighting, weather, camera angles, and edge cases with comprehensive metadata, annotations, and multi-modal sensor support, enabling teams to iterate instantly and train models faster and cheaper than traditional approaches; Synetic AI supports common architectures and export formats, handles edge deployment and monitoring, and can deliver full datasets in about a week and custom trained models in a few weeks. -
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Twine AI
Twine.net
Twine AI offers tailored speech, image, and video data collection and annotation services, including off‑the‑shelf and custom datasets, for training and fine‑tuning AI/ML models. It offers audio (voice recordings, transcription across 163+ languages and dialects), image and video (biometrics, object/scene detection, drone/satellite feeds), text, and synthetic data. Leveraging a vetted global crowd of 400,000–500,000 contributors, Twine ensures ethical, consent‑based collection and bias reduction with ISO 27001-level security and GDPR compliance. Projects are managed end‑to‑end through technical scoping, proofs of concept, and full delivery supported by dedicated project managers, version control, QA workflows, and secure payments across 190+ countries. Its service includes humans‑in‑the‑loop annotation, RLHF techniques, dataset versioning, audit trails, and full dataset management, enabling scalable, context‑rich training data for advanced computer vision. -
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Rendered.ai
Rendered.ai
Overcome challenges in acquiring data for machine learning and AI systems training. Rendered.ai is a PaaS designed for data scientists, engineers, and developers. Generate synthetic datasets for ML/AI training and validation. Experiment with sensor models, scene content, and post-processing effects. Characterize and catalog real and synthetic datasets. Download or move data to your own cloud repositories for processing and training. Power innovation and increase productivity with synthetic data as a capability. Build custom pipelines to model diverse sensors and computer vision inputs. Start quickly with free, customizable Python sample code to model SAR, RGB satellite imagery, and more sensor types. Experiment and iterate with flexible licensing that enables nearly unlimited content generation. Create labeled content rapidly in a hosted, high-performance computing environment. Enable collaboration between data scientists and data engineers with a no-code configuration experience. -
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Rockfish Data
Rockfish Data
Rockfish Data is the industry's first outcome-centric synthetic data generation platform, unlocking the true value of operational data. Rockfish helps enterprises take advantage of siloed data to train ML/AI workflows, produce compelling datasets for product demos, and more. The platform intelligently adapts to and optimizes diverse datasets, seamlessly adjusting to various data types, sources, and structures for maximum efficiency. It focuses on delivering specific, measurable results that drive tangible business value, with a purpose-built architecture emphasizing robust security measures to ensure data integrity and privacy. By operationalizing synthetic data, Rockfish enables organizations to overcome data silos, enhance machine learning and artificial intelligence workflows, and generate high-quality datasets for various applications. -
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Gramosynth
Rightsify
Gramosynth is a powerful AI-driven platform for generating high-quality synthetic music datasets tailored for training next-gen AI models. Leveraging Rightsify’s vast corpus, the system operates on a perpetual data flywheel that continuously ingests freshly released music to generate realistic, copyright-safe audio at professional 48 kHz stereo quality. Datasets include rich, ground-truth metadata such as instrument, genre, tempo, key, and more, structured specifically for advanced model training. It accelerates data collection timelines by up to 99.9%, eliminates licensing bottlenecks, and supports virtually limitless scaling. Integration is seamless via a simple API that allows users to define parameters like genre, mood, instruments, duration, and stems, producing fully annotated datasets with unprocessed stems, FLAC audio, alongside outputs in JSON or CSV formats. -
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syntheticAIdata
syntheticAIdata
syntheticAIdata is your partner in creating synthetic data that enables you to craft diverse datasets effortlessly and at scale. Utilizing our solution doesn’t just mean significant cost reductions; it means ensuring privacy, regulatory compliance, and expediting your AI products' journey to the market. Let syntheticAIdata be the catalyst that transforms your AI aspirations into achievements. Synthetic data is generated on a large scale and can cover many scenarios when real data is insufficient. A variety of annotations can be automatically generated. This greatly shortens the time for data collection and tagging. Minimize costs for data collection and tagging by generating synthetic data on a large scale. Our user-friendly and no-code solution empowers even those without technical expertise to easily generate synthetic data. With seamless one-click integration with leading cloud platforms, our solution is the most convenient to use on the market. -
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Dataocean AI
Dataocean AI
DataOcean AI is a leading provider of high-quality, labeled training data and comprehensive AI data solutions, offering over 1,600 off‑the‑shelf datasets and thousands of customized datasets for machine learning and AI applications. Dataocean's offerings cover diverse modalities (speech, text, image, audio, video, multimodal) and support tasks such as ASR, TTS, NLP, OCR, computer vision, content moderation, machine translation, lexicon development, autonomous driving, and LLM fine‑tuning. It combines AI-driven techniques with human-in-the-loop (HITL) processes via their DOTS platform, which includes over 200 data-processing algorithms and hundreds of labeling tools for automation, assisted labeling, collection, cleaning, annotation, training, and model evaluation. With almost 20 years of experience and presence in more than 70 countries, DataOcean AI ensures strong quality, security, and compliance, serving over 1,000 enterprises and academic institutions globally. -
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MakerSuite
Google
MakerSuite is a tool that simplifies this workflow. With MakerSuite, you’ll be able to iterate on prompts, augment your dataset with synthetic data, and easily tune custom models. When you’re ready to move to code, MakerSuite will let you export your prompt as code in your favorite languages and frameworks, like Python and Node.js. -
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Statice
Statice
We offer data anonymization software that generates entirely anonymous synthetic datasets for our customers. The synthetic data generated by Statice contains statistical properties similar to real data but irreversibly breaks any relationships with actual individuals, making it a valuable and safe to use asset. It can be used for behavior, predictive, or transactional analysis, allowing companies to leverage data safely while complying with data regulations. Statice’s solution is built for enterprise environments with flexibility and security in mind. It integrates features to guarantee the utility and privacy of the data while maintaining usability and scalability. It supports common data types: Generate synthetic data from structured data such as transactions, customer data, churn data, digital user data, geodata, market data, etc We help your technical and compliance teams validate the robustness of our anonymization method and the privacy of your synthetic dataStarting Price: 3,990€/month -
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OneView
OneView
Working exclusively with real data creates significant challenges for machine learning model training. Synthetic data enables limitless machine learning model training, addressing the drawbacks and challenges of real data. Boost the performance of your geospatial analytics by creating the imagery you need. Customizable satellite, drone, and aerial imagery. Create scenarios, change object ratios, and adjust imaging parameters quickly and iteratively. Any rare objects or occurrences can be created. The resulting datasets are fully-annotated, error-free, and ready for training. The OneView simulation engine creates 3D worlds as the base for synthetic satellite and aerial images, layered with multiple randomization factors, filters, and variation parameters. The synthetic images replace real data for remote sensing systems in machine learning model training. They achieve superior interpretation results, especially in cases with limited coverage or poor-quality data. -
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AfterQuery
AfterQuery
AfterQuery is an applied research platform designed to create high-quality training data for frontier artificial intelligence models by capturing how real experts think, reason, and solve problems in professional contexts. It focuses on transforming real-world work into structured datasets that go beyond simple outputs, encoding decision-making processes, tradeoffs, and contextual reasoning that traditional internet-sourced data cannot provide. It works directly with domain experts to generate supervised fine-tuning data, including prompt–response pairs and detailed reasoning traces, as well as reinforcement learning datasets with expert-designed prompts and grading frameworks that convert subjective judgment into scalable reward signals. It also builds custom agent environments across APIs and tools, enabling models to be trained and evaluated in realistic workflows, and captures computer-use trajectories that demonstrate how humans interact with software step by step. -
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SKY ENGINE AI
SKY ENGINE AI
SKY ENGINE AI is a fully managed 3D Generative AI platform that transforms how enterprises build Vision AI by producing high-quality synthetic data at scale. It replaces difficult, expensive real-world data collection with physics-accurate simulation, multispectrum rendering, and automated ground-truth generation. The platform integrates a synthetic data engine, domain adaptation tools, sensor simulators, and deep learning pipelines into a single environment. Teams can test hypotheses, capture rare edge cases, and iterate datasets rapidly using advanced randomization, GAN post-processing, and 3D generative blueprints. With GPU-integrated development tools, distributed rendering, and full cloud resource management, SKY ENGINE AI eliminates workflow complexity and accelerates AI development. The result is faster model training, significantly lower costs, and highly reliable Vision AI across industries. -
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Syntheticus
Syntheticus
Syntheticus® empowers data exchange and overcomes limitations in data access, scarcity, and bias - at scale. With our synthetic data platform, you generate high-quality and compliant data samples tailored to your business needs and analytics goals. With synthetic data, you easily tap into a wide range of high-quality sources that are not always available in the real world. By accessing high-quality, consistent data, you conduct more reliable research, leading to better products, services, and business decisions. With fast, reliable data sources at your fingertips, you accelerate product development cycles and improve time-to-market. Synthetic data is designed to be private and secure by default, protecting sensitive data and maintaining compliance with privacy laws and regulations. -
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Aindo
Aindo
Accelerate time-consuming data processing steps, including structuring, labeling, and preprocessing. Manage your data in one central, easy-to-integrate platform. Increase data accessibility rapidly through privacy-protecting synthetic data and user-friendly exchange platforms. The Aindo synthetic data platform allows you to securely exchange data across departments, with external service providers, partners, and the artificial intelligence community. Explore new synergies through synthetic data exchange and collaboration. Acquire missing data openly and securely. Provide comfort and trust to your clients and stakeholders. The Aindo synthetic data platform removes data inaccuracies and implicit bias for fair and complete insights. Augment information to make databases robust to special events. Balance datasets that misrepresent true populations for a fair and accurate overall depiction. Fill in data gaps in a sound and exact manner. -
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DataHive AI
DataHive AI
DataHive provides high-quality, fully rights-owned datasets across text, image, video, and audio to power modern AI development. The platform sources, creates, and labels data through a global contributor network, ensuring accuracy, diversity, and commercial readiness. DataHive offers specialized datasets including e-commerce listings, customer reviews, multilingual speech, transcribed audio, global video collections, and original photo libraries. Each dataset is enriched with metadata such as pricing, sentiment, tags, engagement metrics, and contextual information. These resources support a wide range of use cases, from computer vision and ASR training to retail analytics, sentiment modeling, and entertainment AI research. Trusted by startups and Fortune 500 companies, DataHive is built to accelerate high-performance machine learning with reliable, scalable data. -
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Gretel
Gretel.ai
Privacy engineering tools delivered to you as APIs. Synthesize and transform data in minutes. Build trust with your users and community. Gretel’s APIs grant immediate access to creating anonymized or synthetic datasets so you can work safely with data while preserving privacy. Keeping the pace with development velocity requires faster access to data. Gretel is accelerating access to data with data privacy tools that bypass blockers and fuel Machine Learning and AI applications. Keep your data contained by running Gretel containers in your own environment or scale out workloads to the cloud in seconds with Gretel Cloud runners. Using our cloud GPUs makes it radically more effortless for developers to train and generate synthetic data. Scale workloads automatically with no infrastructure to set up and manage. Invite team members to collaborate on cloud projects and share data across teams. -
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GenRocket
GenRocket
Enterprise synthetic test data solutions. In order to generate test data that accurately reflects the structure of your application or database, it must be easy to model and maintain each test data project as changes to the data model occur throughout the lifecycle of the application. Maintain referential integrity of parent/child/sibling relationships across the data domains within an application database or across multiple databases used by multiple applications. Ensure the consistency and integrity of synthetic data attributes across applications, data sources and targets. For example, a customer name must always match the same customer ID across multiple transactions simulated by real-time synthetic data generation. Customers want to quickly and accurately create their data model as a test data project. GenRocket offers 10 methods for data model setup. XTS, DDL, Scratchpad, Presets, XSD, CSV, YAML, JSON, Spark Schema, Salesforce. -
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Mistral Forge
Mistral AI
Mistral AI’s Forge platform enables enterprises to build customized AI models tailored to their internal data, workflows, and domain expertise. It provides end-to-end model development capabilities, covering everything from pre-training and synthetic data generation to reinforcement learning and evaluation. Organizations can integrate proprietary datasets and decision frameworks to create models that align closely with their business needs. Forge supports flexible deployment options, allowing companies to run models on-premises, in private cloud environments, or through Mistral infrastructure. The platform emphasizes security and governance, ensuring strict data isolation and compliance with enterprise policies. It also includes advanced evaluation tools that measure performance based on business-specific KPIs rather than generic benchmarks. By managing the full AI lifecycle in one system, Forge helps companies transform institutional knowledge into high-performing AI. -
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MOSTLY AI
MOSTLY AI
As physical customer interactions shift into digital, we can no longer rely on real-life conversations. Customers express their intents, share their needs through data. Understanding customers and testing our assumptions about them also happens through data. And privacy regulations such as GDPR and CCPA make a deep understanding even harder. The MOSTLY AI synthetic data platform bridges this ever-growing gap in customer understanding. A reliable, high-quality synthetic data generator can serve businesses in various use cases. Providing privacy-safe data alternatives is just the beginning of the story. In terms of versatility, MOSTLY AI's synthetic data platform goes further than any other synthetic data generator. MOSTLY AI's versatility and use case flexibility make it a must-have AI tool and a game-changing solution for software development and testing. From AI training to explainability, bias mitigation and governance to realistic test data with subsetting, referential integrity. -
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Synthesized
Synthesized
Power up your AI and data projects with the most valuable data At Synthesized, we unlock data's full potential by automating all stages of data provisioning and data preparation with a cutting-edge AI. We protect from privacy and compliance hurdles by virtue of the data being synthesized through the platform. Software for preparing and provisioning of accurate synthetic data to build better models at scale. Businesses solve the problem of data sharing with Synthesized. 40% of companies investing in AI cannot report business gains. Stay ahead of your competitors and help data scientists, product and marketing teams focus on uncovering critical insight with our simple-to-use platform for data preparation, sanitization and quality assessment. Testing data-driven applications is difficult without representative datasets and this leads to issues when services go live. -
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Luel
Luel AI
Luel is a two-sided AI training data marketplace that connects enterprises and AI teams with a global network of contributors to source, license, and generate high-quality multimodal datasets for machine learning models. It provides curated, rights-cleared datasets that are verified, structured, and ready for training, including video, audio, and image data tailored for use cases such as speech recognition, computer vision, and multimodal AI systems. It enables companies to either browse a catalog of existing datasets or request custom data collection campaigns by specifying detailed requirements such as format, labels, quality standards, and scenarios, which are then fulfilled through a vetted contributor network. Submissions undergo multi-stage validation and quality checks to ensure compliance, accuracy, and usability, delivering enterprise-ready datasets with full licensing and documentation. -
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Synth
Synth
Synth is an open-source data-as-code tool that provides a simple CLI workflow for generating consistent data in a scalable way. Use Synth to generate correct, anonymized data that looks and quacks like production. Generate test data fixtures for your development, testing, and continuous integration. Generate data that tells the story you want to tell. Specify constraints, relations, and all your semantics. Seed development and environments and CI. Anonymize sensitive production data. Create realistic data to your specifications. Synth uses a declarative configuration language that allows you to specify your entire data model as code. Synth can import data straight from existing sources and automatically create accurate and versatile data models. Synth supports semi-structured data and is database agnostic, playing nicely with SQL and NoSQL databases. Synth supports generation for thousands of semantic types such as credit card numbers, email addresses, and more.Starting Price: Free -
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Data is an invaluable business asset. With the right AI model, it’s possible to use data to build and understand customer profiles, look for trends, and identify new business opportunities. But it requires huge volumes of data to develop accurate and robust AI models, and that’s a challenge, from both a data quality and quantity perspective. In addition, stringent regulations, most notably GDPR, restrict the use of certain sensitive data, like customer data. It’s time for a new approach. Especially in a software testing environment where good quality testing data is hard to access. We typically see actual customer data being used, which risks GDPR non-compliance and ensuing heavy financial fines. Artificial Intelligence (AI) is expected to increase business productivity by at least 40% but businesses struggle to deploy or fully unlock AI solutions due to data-related challenges. ADA generates synthetic data using advanced deep learning.
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Sixpack
PumpITup
Sixpack is a data management platform designed to streamline synthetic data for testing purposes. Unlike traditional test data generation, Sixpack provides an endless supply of synthetic data, helping testers and automated tests avoid conflicts and resource bottlenecks. It focuses on flexibility by enabling allocation, pooling, and instant data generation while keeping data quality high and privacy intact. Key features include easy setup, seamless API integration, and the ability to support complex test environments. Sixpack integrates directly with QA processes, so teams save time on managing data dependencies, minimize data overlap, and prevent test interference. Its dashboard offers a clear view of active data sets, and testers can allocate or pool data according to project needs.Starting Price: $0 -
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Lucky Robots
Lucky Robots
Lucky Robots is a robotics-focused simulation platform that lets teams train, test, and refine AI models for robots entirely in high-fidelity virtual environments that mimic real-world physics, sensors, and interactions, enabling massive generation of synthetic training data and rapid iteration without physical robots or costly lab setups. It uses hyper-realistic scenes (e.g., kitchens, terrain) built on advanced simulation tech to create varied edge cases, generate millions of labeled episodes for scalable model learning, and accelerate development while reducing cost and safety risk. It supports natural language control in simulated scenarios, lets users bring their own robot models or choose from commercially available ones, and includes tools for collaboration, environment sharing, and training workflows via LuckyHub, helping developers push models toward real-world performance more efficiently.Starting Price: Free -
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Kled
Kled AI
Kled is a secure, crypto-powered AI data marketplace that connects content rights holders with AI developers by providing high‑quality, ethically sourced datasets, spanning video, audio, music, text, transcripts, and behavioral data, for training generative AI models. It handles end-to-end licensing: it curates, labels, and rates datasets for accuracy and bias, manages contracts and payments securely, and offers custom dataset creation and discovery via a marketplace. Rights holders can upload original content, choose licensing terms, and earn KLED tokens, while developers gain access to premium data for responsible AI model training. Kled also supplies monitoring and recognition tools to ensure authorized usage and to detect misuse. Built for transparency and compliance, the system bridges IP owners and AI builders through a powerful yet user-friendly interface. -
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Private AI
Private AI
Safely share your production data with ML, data science, and analytics teams while safeguarding customer trust. Stop fiddling with regexes and open-source models. Private AI efficiently anonymizes 50+ entities of PII, PCI, and PHI across GDPR, CPRA, and HIPAA in 49 languages with unrivaled accuracy. Replace PII, PCI, and PHI in text with synthetic data to create model training datasets that look exactly like your production data without compromising customer privacy. Remove PII from 10+ file formats, such as PDF, DOCX, PNG, and audio to protect your customer data and comply with privacy regulations. Private AI uses the latest in transformer architectures to achieve remarkable accuracy out of the box, no third-party processing is required. Our technology has outperformed every other redaction service on the market. Feel free to ask us for a copy of our evaluation toolkit to test on your own data. -
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Nixtla
Nixtla
Nixtla is a platform for time-series forecasting and anomaly detection built around its flagship model TimeGPT, described as the first generative AI foundation model for time-series data. It was trained on over 100 billion data points spanning domains such as retail, energy, finance, IoT, healthcare, weather, web traffic, and more, allowing it to make accurate zero-shot predictions across a wide variety of use cases. With just a few lines of code (e.g., via their Python SDK), users can supply historical data and immediately generate forecasts or detect anomalies, even for irregular or sparse time series, and without needing to build or train models from scratch. TimeGPT supports advanced features like handling exogenous variables (e.g., events, prices), forecasting multiple time-series at once, custom loss functions, cross-validation, prediction intervals, and model fine-tuning on bespoke datasets.Starting Price: Free -
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CloudTDMS
Cloud Innovation Partners
CloudTDMS solution is a No-Code platform having all necessary functionalities required for Realistic Data Generation. CloudTDMS, your one stop for Test Data Management. Discover & Profile your Data, Define & Generate Test Data for all your team members : Architects, Developers, Testers, DevOPs, BAs, Data engineers, and more ... CloudTDMS automates the process of creating test data for non-production purposes such as development, testing, training, upgrading or profiling. While at the same time ensuring compliance to regulatory and organisational policies & standards. CloudTDMS involves manufacturing and provisioning data for multiple testing environments by Synthetic Test Data Generation as well as Data Discovery & Profiling. Benefit from CloudTDMS No-Code platform to define your data models and generate your synthetic data quickly in order to get faster return on your “Test Data Management” investments. CloudTDMS solves the following challenges : -Regulatory ComplianceStarting Price: Starter Plan : Always free -
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CUBIG
CUBIG LTD
CUBIG is an AI-ready data infrastructure company that helps enterprises transform raw, restricted, and unstable data into reliable data assets for production AI systems. Its platform enables organizations to make data usable, privacy-safe, and reproducible across AI workflows. CUBIG offers solutions including SynTitan, DTS, and LLM Capsule to address common enterprise AI challenges such as data privacy restrictions, unusable datasets, and inconsistent AI execution. The company uses synthetic data generation, differential privacy, execution state management, and secure AI access controls to prepare enterprise data for AI adoption. CUBIG’s technology helps organizations improve AI reliability while maintaining compliance with regulatory and privacy requirements. The platform supports industries including finance, healthcare, public sector, telecommunications, insurance, retail, and defense. -
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Subsalt
Subsalt Inc.
Subsalt is the first platform built to enable the use of anonymous data at enterprise scale. Subsalt's Query Engine dynamically optimizes the tradeoffs between data privacy and fidelity to the source data. Queries return fully-synthetic data that preserves row-level granularity and data formats without disruptive data transformations. Subsalt provides compliance guarantees supported by third-party audits that satisfy HIPAA's Expert Determination standard. Subsalt supports multiple deployment models to meet the unique privacy and security requirements of each client. Subsalt is SOC2-Type 2 and HIPAA compliant. The system has been designed to minimize the risk of exposure or breach of real data. Existing data and ML tools integrate directly with Subsalt's Postgres-compatible SQL interface, making adoption a breeze. -
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Shaip
Shaip
Shaip offers end-to-end generative AI services, specializing in high-quality data collection and annotation across multiple data types including text, audio, images, and video. The platform sources and curates diverse datasets from over 60 countries, supporting AI and machine learning projects globally. Shaip provides precise data labeling services with domain experts ensuring accuracy in tasks like image segmentation and object detection. It also focuses on healthcare data, delivering vast repositories of physician audio, electronic health records, and medical images for AI training. With multilingual audio datasets covering 60+ languages and dialects, Shaip enhances conversational AI development. The company ensures data privacy through de-identification services, protecting sensitive information while maintaining data utility. -
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Mimic
Facteus
Advanced technology and services to safely transform and enhance sensitive data into actionable insights, help drive innovation, and open new revenue streams. Using the Mimic synthetic data engine, companies can safely synthesize their data assets, protecting consumer privacy information from being exposed, while still maintaining the statistical relevancy of the data. The synthetic data can then be used for internal initiatives like analytics, machine learning and AI, marketing and segmentation activities, and new revenue streams through external data monetization. Mimic enables you to safely move statistically-relevant synthetic data to the cloud ecosystem of your choice to get the most out of your data. Analytics, insights, product development, testing, and third-party data sharing can all be done in the cloud with the enhanced synthetic data, which has been certified to be compliant with regulatory and privacy laws. -
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Synthesis AI
Synthesis AI
A synthetic data platform for ML engineers to enable the development of more capable AI models. Simple APIs provide on-demand generation of perfectly-labeled, diverse, and photoreal images. Highly-scalable cloud-based generation platform delivers millions of perfectly labeled images. On-demand data enables new data-centric approaches to develop more performant models. An expanded set of pixel-perfect labels including segmentation maps, dense 2D/3D landmarks, depth maps, surface normals, and much more. Rapidly design, test, and refine your products before building hardware. Prototype different imaging modalities, camera placements, and lens types to optimize your system. Reduce bias in your models associated with misbalanced data sets while preserving privacy. Ensure equal representation across identities, facial attributes, pose, camera, lighting, and much more. We have worked with world-class customers across many use cases. -
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Scale Data Engine
Scale AI
Scale Data Engine helps ML teams build better datasets. Bring together your data, ground truth, and model predictions to effortlessly fix model failures and data quality issues. Optimize your labeling spend by identifying class imbalance, errors, and edge cases in your data with Scale Data Engine. Significantly improve model performance by uncovering and fixing model failures. Find and label high-value data by curating unlabeled data with active learning and edge case mining. Curate the best datasets by collaborating with ML engineers, labelers, and data ops on the same platform. Easily visualize and explore your data to quickly find edge cases that need labeling. Check how well your models are performing and always ship the best one. Easily view your data, metadata, and aggregate statistics with rich overlays, using our powerful UI. Scale Data Engine supports visualization of images, videos, and lidar scenes, overlaid with all associated labels, predictions, and metadata. -
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Neurolabs
Neurolabs
Industry-leading technology powered by synthetic data for flawless retail execution. The new wave of vision technology for consumer packaged goods. Select from an extensive catalog of over 100,000 SKUs in the Neurolabs platform including top brands such as P&G, Nestlé, Unilever, Coca-Cola, and much more. Your field agents can upload multiple shelf images from mobile devices to our API which will automatically stitch the images together to generate the scene. SKU-level detection provides you with detailed information to compute retail execution KPIs such as out-of-shelf rate, shelf share percentage, competitor price comparison, and so much more! Discover how our cutting-edge image recognition technology can help you maximize store operations, enhance customer experience, and boost profitability. Implement a real-world deployment in less than 1 week. Access image recognition datasets for over 100,000 SKUs. -
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Datomize
Datomize
Our AI-powered data generation platform enables data analysts and machine learning engineers to maximize the value of their analytical data sets. By leveraging the behavior extracted from existing data, Datomize enables users to generate the exact analytical data sets needed. Equipped with data that comprehensively represent real-world scenarios, users can now gain a far more accurate reflection of reality and make much better decisions. Extract superior insights from your data and develop state-of-the-art AI solutions. Datomize’s AI-powered, generative models create superior synthetic replicas by extracting the behavior from your existing data. Advanced augmentation capabilities enable limitless resizing of your data, while dynamic validation tools visualize the similarity between original and replicated data sets. Datomize’s data-centric approach to machine learning addresses the primary data constraints of training high-performing ML models.Starting Price: $720 per month -
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Amazon SageMaker Ground Truth
Amazon Web Services
Amazon SageMaker allows you to identify raw data such as images, text files, and videos; add informative labels and generate labeled synthetic data to create high-quality training data sets for your machine learning (ML) models. SageMaker offers two options, Amazon SageMaker Ground Truth Plus and Amazon SageMaker Ground Truth, which give you the flexibility to use an expert workforce to create and manage data labeling workflows on your behalf or manage your own data labeling workflows. data labeling. If you want the flexibility to create and manage your own personal and data labeling workflows, you can use SageMaker Ground Truth. SageMaker Ground Truth is a data labeling service that makes data labeling easy and gives you the option of using human annotators via Amazon Mechanical Turk, third-party providers, or your own private staff.Starting Price: $0.08 per month -
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Keymakr
Keymakr
Keymakr provides image and video data annotation, along with data creation, collection, and validation services for AI and machine learning computer vision projects of any scale. The company’s core expertise lies in delivering high-quality training data for multimodal and embodied AI systems, and supporting human-verified annotation and LLM ground-truth validation of model outputs. Keymakr's motto, "Human teaching for machine learning," reflects its commitment to the human-in-the-loop approach. This is why the company maintains an in-house team of over 600 highly skilled annotators. Keymakr's goal is to deliver custom datasets that enhance the accuracy and efficiency of ML systems. To create precise datasets, Keymakr developed Keylabs.ai, a powerful enterprise-grade annotation platform that supports all annotation types. Keymakr also follows strict data security and compliance standards, holds ISO 9001 and ISO 27001 certifications, and maintains GDPR and HIPAA compliance.Starting Price: $7/hour