Alternatives to Subsalt

Windocks provides on-demand Oracle, SQL Server, as well as other databases that can be customized for Dev, Test, Reporting, ML, DevOps, and DevOps. Windocks database orchestration allows for code-free end to end automated delivery. This includes masking, synthetic data, Git operations and access controls, as well as secrets management. Databases can be delivered to conventional instances, Kubernetes or Docker containers. Windocks can be installed on standard Linux or Windows servers in minutes. It can also run on any public cloud infrastructure or on-premise infrastructure. One VM can host up 50 concurrent database environments. When combined with Docker containers, enterprises often see a 5:1 reduction of lower-level database VMs.

Mask, generate, subset, virtualize, and automate your test data with the DATPROF Test Data Management Suite. Our solution helps managing Personally Identifiable Information and/or too large databases. Long waiting times for test data refreshes are a thing of the past.

Titaniam provides enterprises and SaaS vendors with a full suite of data security controls in one solution. This includes highly advanced options such as encrypted search and analytics, and also traditional controls such as tokenization, masking, various types of encryption, and anonymization. Titaniam also offers BYOK/HYOK (bring/hold your own key) for data owners to control the security of their data. When attacked, Titaniam minimizes regulatory overhead by providing evidence that sensitive data retained encryption. Titaniam’s interoperable modules can be combined to support hundreds of architectures across multiple clouds, on-prem, and hybrid environments. Titaniam provides the equivalent of at 3+ solutions making it the most effective, and economical solution in the market. Titaniam is featured by Gartner across multiple categories in four markets (Data Security, Data Privacy, Enterprise Key Management, and as a Cool Vendor for 2022). Titaniam is also a TAG Cyber Distinguished Vendor, and an Intellyx Digital Innovator for 2022. In 2022 Titaniam won the coveted SINET16 Security Innovator Award and was also a winner in four categories for the Global Infosec Awards at RSAC2022.

IRI FieldShield® is a powerful and affordable data discovery and de-identification package for masking PII, PHI, PAN and other sensitive data in structured and semi-structured sources. Front-ended in a free Eclipse-based design environment, FieldShield jobs classify, profile, scan, and de-identify data at rest (static masking). Use the FieldShield SDK or proxy-based application to secure data in motion (dynamic data masking). The usual method for masking RDB and other flat files (CSV, Excel, LDIF, COBOL, etc.) is to classify it centrally, search for it globally, and automatically mask it in a consistent way using encryption, pseudonymization, redaction or other functions to preserve realism and referential integrity in production or test environments. Use FieldShield to make test data, nullify breaches, or comply with GDPR. HIPAA. PCI, PDPA, PCI-DSS and other laws. Audit through machine- and human-readable search reports, job logs and re-ID risks scores. Optionally mask data when you map it; FieldShield functions can also run in IRI Voracity ETL and federation, migration, replication, subsetting, and analytic jobs. To mask DB clones run FieldShield in Windocks, Actifio or Commvault. Call it from CI/CD pipelines and apps.

IRI Voracity is an end-to-end software platform for fast, affordable, and ergonomic data lifecycle management. Voracity speeds, consolidates, and often combines the key activities of data discovery, integration, migration, governance, and analytics in a single pane of glass, built on Eclipse™. Through its revolutionary convergence of capability and its wide range of job design and runtime options, Voracity bends the multi-tool cost, difficulty, and risk curves away from megavendor ETL packages, disjointed Apache projects, and specialized software. Voracity uniquely delivers the ability to perform data: * profiling and classification * searching and risk-scoring * integration and federation * migration and replication * cleansing and enrichment * validation and unification * masking and encryption * reporting and wrangling * subsetting and testing Voracity runs on-premise, or in the cloud, on physical or virtual machines, and its runtimes can also be containerized or called from real-time applications or batch jobs.

K2View believes that every enterprise should be able to leverage its data to become as disruptive and agile as possible. We enable this through our Data Product Platform, which creates and manages a trusted dataset for every business entity – on demand, in real time. The dataset is always in sync with its sources, adapts to changes on the fly, and is instantly accessible to any authorized data consumer. We fuel operational use cases, including customer 360, data masking, test data management, data migration, and legacy application modernization – to deliver business outcomes at half the time and cost of other alternatives.

Share your production data with machine learning, data science, and analytics teams securely while maintaining customer trust. Eliminate the hassle of using regexes and open-source models. Private AI skillfully anonymizes over 50 types of personally identifiable information (PII), payment card information (PCI), and protected health information (PHI) in compliance with GDPR, CPRA, and HIPAA across 49 languages with exceptional precision. Substitute PII, PCI, and PHI in your text with synthetic data to generate model training datasets that accurately resemble your original data while ensuring customer privacy remains intact. Safeguard your customer information by removing PII from more than 10 file formats, including PDF, DOCX, PNG, and audio files, to adhere to privacy laws. Utilizing cutting-edge transformer architectures, Private AI delivers outstanding accuracy without the need for third-party processing. Our solution has surpassed all other redaction services available in the industry. Request our evaluation toolkit, and put our technology to the test with your own data to see the difference for yourself. With Private AI, you can confidently navigate regulatory landscapes while still leveraging valuable insights from your data.

Statice is a data anonymization tool that draws on the most recent data privacy research. It processes sensitive data to create anonymous synthetic datasets that retain all the statistical properties of the original data. Statice's solution was designed for enterprise environments that are flexible and secure. It incorporates features that guarantee privacy and utility of data while maintaining usability.

The hours dedicated to manually anonymizing data detract from essential work tasks. When data is not easily accessible, it becomes trapped, resulting in organizational silos and inefficient knowledge management. Furthermore, there is an ongoing concern about whether the shared data complies with constantly changing regulations such as GDPR, CCPA, and HIPAA. Nymiz addresses these challenges by securely anonymizing personal data using both reversible and irreversible techniques. Original data is substituted with asterisks, tokens, or synthetic surrogates, enhancing privacy while preserving the information's utility. By effectively identifying context-specific data such as names, phone numbers, and social security numbers, our solution delivers superior outcomes compared to conventional tools that lack artificial intelligence features. Additionally, we incorporate an extra security layer at the data level to safeguard against breaches. Ultimately, anonymized or pseudonymized data loses its value if it can be compromised through security vulnerabilities or human mistakes, underscoring the importance of robust protection measures.

Tonic provides an automated solution for generating mock data that retains essential features of sensitive datasets, enabling developers, data scientists, and sales teams to operate efficiently while ensuring confidentiality. By simulating your production data, Tonic produces de-identified, realistic, and secure datasets suitable for testing environments. The data is crafted to reflect your actual production data, allowing you to convey the same narrative in your testing scenarios. With Tonic, you receive safe and practical data designed to emulate your real-world data at scale. This tool generates data that not only resembles your production data but also behaves like it, facilitating safe sharing among teams, organizations, and across borders. It includes features for identifying, obfuscating, and transforming personally identifiable information (PII) and protected health information (PHI). Tonic also ensures the proactive safeguarding of sensitive data through automatic scanning, real-time alerts, de-identification processes, and mathematical assurances of data privacy. Moreover, it offers advanced subsetting capabilities across various database types. In addition to this, Tonic streamlines collaboration, compliance, and data workflows, delivering a fully automated experience to enhance productivity. With such robust features, Tonic stands out as a comprehensive solution for data security and usability, making it indispensable for organizations dealing with sensitive information.

Gretel provides privacy engineering solutions through APIs that enable you to synthesize and transform data within minutes. By utilizing these tools, you can foster trust with your users and the broader community. With Gretel's APIs, you can quickly create anonymized or synthetic datasets, allowing you to handle data safely while maintaining privacy. As development speeds increase, the demand for rapid data access becomes essential. Gretel is at the forefront of enhancing data access with privacy-focused tools that eliminate obstacles and support Machine Learning and AI initiatives. You can maintain control over your data by deploying Gretel containers within your own infrastructure or effortlessly scale to the cloud using Gretel Cloud runners in just seconds. Leveraging our cloud GPUs significantly simplifies the process for developers to train and produce synthetic data. Workloads can be scaled automatically without the need for infrastructure setup or management, fostering a more efficient workflow. Additionally, you can invite your team members to collaborate on cloud-based projects and facilitate data sharing across different teams, further enhancing productivity and innovation.

Maintain the essence, structure, and accuracy while ensuring confidentiality. Improve data security by anonymizing and altering sensitive information, as well as implementing pseudonymization strategies for adherence to privacy regulations and analytics purposes. The obscured data continues to hold its context and referential integrity, making it suitable for use in testing, analytics, or support scenarios. Serving as an exceptionally scalable and high-performing data masking solution, Informatica Persistent Data Masking protects sensitive information—like credit card details, addresses, and phone numbers—from accidental exposure by generating realistic, anonymized data that can be safely shared both internally and externally. Additionally, this solution minimizes the chances of data breaches in nonproduction settings, enhances the quality of test data, accelerates development processes, and guarantees compliance with various data-privacy laws and guidelines. Ultimately, adopting such robust data masking techniques not only protects sensitive information but also fosters trust and security within organizations.

Protect sensitive information at every stage—whether on-site, in the cloud, or within extensive data analytic systems. Voltage encryption provides a robust solution for data privacy, mitigates the risks associated with data breaches, and enhances business value through the secure utilization of data. Implementing effective data protection fosters customer trust and ensures adherence to international regulations such as GDPR, CCPA, and HIPAA. Privacy laws advocate for methods like encryption, pseudonymization, and anonymization to safeguard personal information. Voltage SecureData empowers organizations to anonymize sensitive structured data while still allowing its use in a secure manner, facilitating business growth. It's essential to guarantee that applications function on secure data that moves seamlessly through the organization, without any vulnerabilities, decryption requirements, or negative impacts on performance. SecureData is compatible with a wide array of platforms and can encrypt data in various programming languages. Additionally, the Structured Data Manager incorporates SecureData, enabling companies to protect their data efficiently and continuously throughout its entire lifecycle, from initial discovery all the way to encryption. This comprehensive approach not only enhances security but also streamlines data management processes.

A platform designed for ML engineers that generates synthetic data, facilitating the creation of more advanced AI models. With straightforward APIs, users can quickly generate a wide variety of perfectly-labeled, photorealistic images as needed. This highly scalable, cloud-based system can produce millions of accurately labeled images, allowing for innovative data-centric strategies that improve model performance. The platform offers an extensive range of pixel-perfect labels, including segmentation maps, dense 2D and 3D landmarks, depth maps, and surface normals, among others. This capability enables rapid design, testing, and refinement of products prior to hardware implementation. Additionally, it allows for prototyping with various imaging techniques, camera positions, and lens types to fine-tune system performance. By minimizing biases linked to imbalanced datasets while ensuring privacy, the platform promotes fair representation across diverse identities, facial features, poses, camera angles, lighting conditions, and more. Collaborating with leading customers across various applications, our platform continues to push the boundaries of AI development. Ultimately, it serves as a pivotal resource for engineers seeking to enhance their models and innovate in the field.

Cutting-edge technology and services are designed to securely transform and elevate sensitive information into actionable insights, thereby fostering innovation and creating new avenues for revenue generation. Through the use of the Mimic synthetic data engine, businesses can effectively synthesize their data assets, ensuring that consumer privacy is safeguarded while preserving the statistical relevance of the information. This synthetic data can be leveraged for a variety of internal initiatives, such as analytics, machine learning, artificial intelligence, marketing efforts, and segmentation strategies, as well as for generating new revenue streams via external data monetization. Mimic facilitates the secure transfer of statistically relevant synthetic data to any cloud platform of your preference, maximizing the utility of your data. In the cloud, enhanced synthetic data—validated for compliance with regulatory and privacy standards—can support analytics, insights, product development, testing, and collaboration with third-party data providers. This dual focus on innovation and compliance ensures that organizations can harness the power of their data without compromising on privacy.

Modern enterprises encounter severe repercussions if they fail to comply with the growing privacy standards set by regulators and the public alike. To stay competitive, vendors must continuously integrate advanced algorithms aimed at safeguarding sensitive information such as Personally Identifiable Information (PII) and Protected Health Information (PHI). HushHush leads the way in privacy defense through its innovative PII data discovery and anonymization tool, which is also referred to as data de-identification, data masking, and obfuscation software. This tool assists organizations in locating, classifying, and anonymizing sensitive data, ensuring compliance with regulations like GDPR, CCPA, HIPAA/HITECH, and GLBA. It offers a suite of rule-based atomic add-on components that empower users to build robust and secure data anonymization strategies. HushHush's solutions are pre-configured to effectively anonymize both direct identifiers, such as Social Security Numbers and credit card information, as well as indirect identifiers, utilizing a combination of fixed algorithms tailored for this purpose. With such versatile capabilities, HushHush not only enhances data security but also fortifies trust with clients regarding their privacy.

To protect sensitive information, including personally identifiable information (PII), organizations must implement techniques such as pseudonymization and anonymization for secondary purposes like comparative effectiveness studies, policy evaluations, and research in life sciences. This process is essential as businesses amass vast quantities of data to detect patterns, understand customer behavior, and foster innovation. Compliance with regulations like HIPAA and GDPR mandates the de-identification of data; however, the difficulty lies in the fact that many de-identification tools prioritize the removal of personal identifiers, often complicating subsequent data usage. By transforming PII into forms that cannot be traced back to individuals, employing data anonymization and pseudonymization strategies becomes crucial for maintaining privacy while enabling robust analysis. Effectively utilizing these methods allows for the examination of extensive datasets without infringing on privacy laws, ensuring that insights can be gathered responsibly. Selecting appropriate de-identification techniques and privacy models from a wide range of data security and statistical practices is key to achieving effective data usage.

The increasing risks to security and the rise of stringent privacy laws have necessitated a more cautious approach to handling sensitive information. Oracle Data Masking and Subsetting offers database users a solution to enhance security, streamline compliance efforts, and lower IT expenses by sanitizing production data copies for use in testing, development, and various other functions, while also allowing for the removal of superfluous data. This tool allows for the extraction, obfuscation, and sharing of both full copies and subsets of application data with partners, whether they are within or outside the organization. By doing so, it ensures the database's integrity remains intact, thus supporting the ongoing functionality of applications. Additionally, Application Data Modeling automatically identifies columns within Oracle Database tables that contain sensitive data through established discovery patterns, including national IDs, credit card details, and other forms of personally identifiable information. Furthermore, it can recognize and map parent-child relationships that are defined within the database structure, enhancing the overall data management process.

Protecting your personal information is crucial, and it’s essential to create data that appears genuine for software development purposes. To achieve this, DOT Anonymizer provides a solution that effectively masks your testing data while maintaining its consistency across various data sources and database management systems. The risk of data breaches arises significantly when using personal or identifiable information in non-production environments such as development, testing, training, and business intelligence. With the growing number of regulations worldwide, organizations are increasingly required to anonymize or pseudonymize sensitive information. This process allows you to keep the original format of the data while your teams can operate with believable yet fictional datasets. It is vital to manage all your data sources effectively to ensure their continued utility. You can easily invoke DOT Anonymizer functions directly from your applications, ensuring consistent anonymization across all database management systems and platforms. Additionally, it’s important to maintain relationships between tables to guarantee that the data remains realistic. The tool is capable of anonymizing a variety of database types and file formats, including CSV, XML, JSON, and more. As the demand for data protection grows, utilizing a solution like DOT Anonymizer becomes increasingly essential for maintaining the integrity and confidentiality of your data.

The Synthetic Data Vault (SDV) is a comprehensive Python library crafted for generating synthetic tabular data with ease. It employs various machine learning techniques to capture and replicate the underlying patterns present in actual datasets, resulting in synthetic data that mirrors real-world scenarios. The SDV provides an array of models, including traditional statistical approaches like GaussianCopula and advanced deep learning techniques such as CTGAN. You can produce data for individual tables, interconnected tables, or even sequential datasets. Furthermore, it allows users to assess the synthetic data against real data using various metrics, facilitating a thorough comparison. The library includes diagnostic tools that generate quality reports to enhance understanding and identify potential issues. Users also have the flexibility to fine-tune data processing for better synthetic data quality, select from various anonymization techniques, and establish business rules through logical constraints. Synthetic data can be utilized as a substitute for real data to increase security, or as a complementary resource to augment existing datasets. Overall, the SDV serves as a holistic ecosystem for synthetic data models, evaluations, and metrics, making it an invaluable resource for data-driven projects. Additionally, its versatility ensures it meets a wide range of user needs in data generation and analysis.

Safeguard your data comprehensively with a robust, enterprise-level security solution that spans multicloud, hybrid, and on-premises environments, accommodating all types of data. Enhance security measures across diverse platforms while seamlessly discovering and categorizing structured, semi-structured, and unstructured data. Assess and prioritize data risks by considering both incident context and the potential for additional capabilities. Streamline data management through a unified service or dashboard that centralizes oversight. Guard against unauthorized data exposure and prevent breaches effectively. Make data-centric security, compliance, and governance processes simpler and more efficient. Create a consolidated perspective to glean insights on vulnerable data and users, while actively managing a Zero Trust framework and enforcing relevant policies. Leverage automation and workflows to save both time and resources, and ensure support for a wide range of file shares and data repositories, including those in public, private, data center, and third-party cloud environments. Address not only your current requirements but also future integrations as you evolve and expand cloud use cases, thereby enhancing your overall data security strategy. By implementing these measures, you can significantly bolster your organization’s resilience against data-related threats.

Streamline the lengthy processes of data handling, such as structuring, labeling, and preprocessing tasks. Centralize your data management within a single, easily integrable platform for enhanced efficiency. Rapidly enhance data accessibility through the use of synthetic data that prioritizes privacy and user-friendly exchange platforms. With the Aindo synthetic data platform, securely share data not only within your organization but also with external service providers, partners, and the AI community. Uncover new opportunities for collaboration and synergy through the exchange of synthetic data. Obtain any missing data in a manner that is both secure and transparent. Instill a sense of trust and reliability in your clients and stakeholders. The Aindo synthetic data platform effectively eliminates inaccuracies and biases, leading to fair and comprehensive insights. Strengthen your databases to withstand exceptional circumstances by augmenting the information they contain. Rectify datasets that fail to represent true populations, ensuring a more equitable and precise overall representation. Methodically address data gaps to achieve sound and accurate results. Ultimately, these advancements not only enhance data quality but also foster innovation and growth across various sectors.

syntheticAIdata serves as your ally in producing synthetic datasets that allow for easy and extensive creation of varied data collections. By leveraging our solution, you not only achieve substantial savings but also maintain privacy and adhere to regulations, all while accelerating the progression of your AI products toward market readiness. Allow syntheticAIdata to act as the driving force in turning your AI dreams into tangible successes. With the capability to generate vast amounts of synthetic data, we can address numerous scenarios where actual data is lacking. Additionally, our system can automatically produce a wide range of annotations, significantly reducing the time needed for data gathering and labeling. By opting for large-scale synthetic data generation, you can further cut down on expenses related to data collection and tagging. Our intuitive, no-code platform empowers users without technical knowledge to effortlessly create synthetic data. Furthermore, the seamless one-click integration with top cloud services makes our solution the most user-friendly option available, ensuring that anyone can easily access and utilize our groundbreaking technology for their projects. This ease of use opens up new possibilities for innovation in diverse fields.

As enterprise data explodes and is scattered across multiple systems, the oversight of privacy, data security and governance has become a very difficult task. Businesses are exposed to significant risks, including data breaches, privacy suits, and penalties. It takes months to find data privacy risks within an organization. A team of data engineers is involved in the effort. Data breaches and privacy legislation are forcing companies to better understand who has access to data and how it is used. Enterprise data is complex. Even if a team works for months to isolate data privacy risks, they may not be able to quickly find ways to reduce them.

Embracing data-centric AI has become remarkably straightforward thanks to advancements in automated data quality profiling and synthetic data creation. Our solutions enable data scientists to harness the complete power of their data. YData Fabric allows users to effortlessly navigate and oversee their data resources, providing synthetic data for rapid access and pipelines that support iterative and scalable processes. With enhanced data quality, organizations can deliver more dependable models on a larger scale. Streamline your exploratory data analysis by automating data profiling for quick insights. Connecting to your datasets is a breeze via a user-friendly and customizable interface. Generate synthetic data that accurately reflects the statistical characteristics and behaviors of actual datasets. Safeguard your sensitive information, enhance your datasets, and boost model efficiency by substituting real data with synthetic alternatives or enriching existing datasets. Moreover, refine and optimize workflows through effective pipelines by consuming, cleaning, transforming, and enhancing data quality to elevate the performance of machine learning models. This comprehensive approach not only improves operational efficiency but also fosters innovative solutions in data management.

Syntheticus® revolutionizes the way organizations exchange data, addressing challenges related to data accessibility, scarcity, and inherent biases on a large scale. Our synthetic data platform enables you to create high-quality, compliant data samples that align seamlessly with your specific business objectives and analytical requirements. By utilizing synthetic data, you gain access to a diverse array of premium sources that may not be readily available in the real world. This access to quality and consistent data enhances the reliability of your research, ultimately resulting in improved products, services, and decision-making processes. With swift and dependable data resources readily available, you can expedite your product development timelines and optimize market entry. Furthermore, synthetic data is inherently designed to prioritize privacy and security, safeguarding sensitive information while ensuring adherence to relevant privacy laws and regulations. This forward-thinking approach not only mitigates risks but also empowers businesses to innovate with confidence.

Effortlessly create a wide variety of realistic synthetic data and detailed 3D environments to boost model efficacy. Bifrost's platform stands out as the quickest solution for producing the high-quality synthetic images necessary to enhance machine learning performance and address the limitations posed by real-world datasets. By bypassing the expensive and labor-intensive processes of data collection and annotation, you can prototype and test up to 30 times more efficiently. This approach facilitates the generation of data that represents rare scenarios often neglected in actual datasets, leading to more equitable and balanced collections. The traditional methods of manual annotation and labeling are fraught with potential errors and consume significant resources. With Bifrost, you can swiftly and effortlessly produce data that is accurately labeled and of pixel-perfect quality. Furthermore, real-world data often reflects the biases present in the conditions under which it was gathered, and synthetic data generation provides a valuable solution to mitigate these biases and create more representative datasets. By utilizing this advanced platform, researchers can focus on innovation rather than the cumbersome aspects of data preparation.

Sixpack is an innovative data management solution designed to enhance the creation of synthetic data specifically for testing scenarios. In contrast to conventional methods of test data generation, Sixpack delivers a virtually limitless supply of synthetic data, which aids testers and automated systems in sidestepping conflicts and avoiding resource constraints. It emphasizes adaptability by allowing for allocation, pooling, and immediate data generation while ensuring high standards of data quality and maintaining privacy safeguards. Among its standout features are straightforward setup procedures, effortless API integration, and robust support for intricate testing environments. By seamlessly fitting into quality assurance workflows, Sixpack helps teams save valuable time by reducing the management burden of data dependencies, minimizing data redundancy, and averting test disruptions. Additionally, its user-friendly dashboard provides an organized overview of current data sets, enabling testers to efficiently allocate or pool data tailored to the specific demands of their projects, thereby optimizing the testing process further.

As interactions with customers increasingly transition from physical to digital environments, it becomes necessary to move beyond traditional face-to-face conversations. Instead, customers now convey their preferences and requirements through data. Gaining insights into customer behavior and validating our preconceptions about them also relies heavily on data-driven approaches. However, stringent privacy laws like GDPR and CCPA complicate this deep understanding even further. The MOSTLY AI synthetic data platform effectively addresses this widening gap in customer insights. This reliable and high-quality synthetic data generator supports businesses across a range of applications. Offering privacy-compliant data alternatives is merely the starting point of its capabilities. In terms of adaptability, MOSTLY AI's synthetic data platform outperforms any other synthetic data solution available. The platform's remarkable versatility and extensive use case applicability establish it as an essential AI tool and a transformative resource for software development and testing. Whether for AI training, enhancing explainability, mitigating bias, ensuring governance, or generating realistic test data with subsetting and referential integrity, MOSTLY AI serves a broad spectrum of needs. Ultimately, its comprehensive features empower organizations to navigate the complexities of customer data while maintaining compliance and protecting user privacy.

Rockfish Data represents the pioneering solution in the realm of outcome-focused synthetic data generation, effectively revealing the full potential of operational data. The platform empowers businesses to leverage isolated data for training machine learning and AI systems, creating impressive datasets for product presentations, among other uses. With its ability to intelligently adapt and optimize various datasets, Rockfish offers seamless adjustments to different data types, sources, and formats, ensuring peak efficiency. Its primary goal is to deliver specific, quantifiable outcomes that contribute real business value while featuring a purpose-built architecture that prioritizes strong security protocols to maintain data integrity and confidentiality. By transforming synthetic data into a practical asset, Rockfish allows organizations to break down data silos, improve workflows in machine learning and artificial intelligence, and produce superior datasets for a wide range of applications. This innovative approach not only enhances operational efficiency but also promotes a more strategic use of data across various sectors.

Datagen offers a self-service platform designed for creating synthetic data tailored specifically for visual AI applications, with an emphasis on both human and object data. This platform enables users to exert detailed control over the data generation process, facilitating the analysis of neural networks to identify the precise data required for enhancement. Users can effortlessly produce that targeted data to train their models effectively. To address various challenges in data generation, Datagen equips teams with a robust platform capable of producing high-quality, diverse synthetic data that is specific to particular domains. It also includes sophisticated features that allow for the simulation of dynamic humans and objects within their respective contexts. With Datagen, computer vision teams gain exceptional flexibility in managing visual results across a wide array of 3D environments, while also having the capability to establish distributions for every element of the data without any inherent biases, ensuring a fair representation in the generated datasets. This comprehensive approach empowers teams to innovate and refine their AI models with precision and efficiency.

Elevate your AI and data initiatives by harnessing the power of premium data. At Synthesized, we fully realize the potential of data by utilizing advanced AI to automate every phase of data provisioning and preparation. Our innovative platform ensures adherence to privacy and compliance standards, thanks to the synthesized nature of the data it generates. We offer software solutions for crafting precise synthetic data, enabling organizations to create superior models at scale. By partnering with Synthesized, businesses can effectively navigate the challenges of data sharing. Notably, 40% of companies investing in AI struggle to demonstrate tangible business benefits. Our user-friendly platform empowers data scientists, product managers, and marketing teams to concentrate on extracting vital insights, keeping you ahead in a competitive landscape. Additionally, the testing of data-driven applications can present challenges without representative datasets, which often results in complications once services are launched. By utilizing our services, organizations can significantly mitigate these risks and enhance their operational efficiency.

Syntho is generally implemented within our clients' secure environments to ensure that sensitive information remains within a trusted setting. With our ready-to-use connectors, you can establish connections to both source data and target environments effortlessly. We support integration with all major databases and file systems, offering more than 20 database connectors and over 5 file system connectors. You have the ability to specify your preferred method of data synthetization, whether it involves realistic masking or the generation of new values, along with the automated identification of sensitive data types. Once the data is protected, it can be utilized and shared safely, upholding compliance and privacy standards throughout its lifecycle, thus fostering a secure data handling culture.

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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 ... 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 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. CloudTDMS is a No-code platform for your Test Data Management, it provides you everything you need to make your data development & testing go super fast! Especially, CloudTDMS solves the following challenges : -Regulatory Compliance -Test Data Readiness -Data profiling -Automation

Our innovative automation platform, powered by AI and designed for low-code usage, aims to deliver exceptional results in the least amount of time. With our Natural Language Processing (NLP) technology, you can effortlessly generate automation scripts in plain English, freeing your developers to concentrate on innovative projects. Throughout your application's lifecycle, you can maintain high quality thanks to our autonomous discovery feature and comprehensive tracking of any changes. Our autonomous healing capabilities help mitigate risks in your ever-evolving development landscape, ensuring that updates are seamless and current. To comply with all regulatory standards and enhance security, utilize AI-generated synthetic data tailored to your automation requirements. Additionally, you can conduct multiple tests simultaneously, adjust test frequencies, and keep up with browser updates across diverse operating systems and platforms, ensuring a smooth user experience. This comprehensive approach not only streamlines your processes but also enhances overall productivity and efficiency.

The MDClone ADAMS Platform serves as a robust, self-service environment for data analytics that facilitates collaboration, research, and innovation within the healthcare sector. With this groundbreaking platform, users gain real-time, dynamic, secure, and independent access to valuable insights, effectively dismantling obstacles to healthcare data exploration. This empowers organizations to embark on a journey of continuous learning that enhances patient care, optimizes operations, encourages research initiatives, and fosters innovation, thereby driving actionable outcomes throughout the entire healthcare ecosystem. Additionally, the use of synthetic data allows for seamless collaboration among teams, organizations, and external partners, enabling them to delve into the essential information they require precisely when it is needed. By tapping into real-world data sourced directly from within health systems, life science organizations can pinpoint promising patient cohorts for detailed post-marketing analysis. Ultimately, this innovative approach transforms the way healthcare data is accessed and utilized for life sciences, paving the way for unprecedented advancements in the field. As a result, stakeholders can make informed decisions that significantly impact patient outcomes and overall healthcare quality.

Ensure the safe storage, anonymization, masking, mining, redaction, and sharing of sensitive information while achieving complete accuracy and adhering to global data privacy regulations. By effectively separating personally identifiable information (PII) from identified data, you can enjoy substantial time and cost efficiencies without sacrificing functionality. Integrate PII Vault to foster groundbreaking solutions, accelerate your time to market, and provide unparalleled security for PII across all platforms. This approach enables you to harness data for creating more precise and targeted communications. Simplify the process with a straightforward method to anonymize all data prior to its entry into your system. Utilize Poly-Anonymization™ to merge various anonymous data sets at the individual level without ever accessing PII post-anonymization. Furthermore, substitute PII with a compliant, multi-valued, non-identifying key that facilitates anonymous data matching across different organizations, enhancing collaborative efforts while maintaining privacy. This comprehensive strategy not only protects individual identities but also empowers organizations to derive meaningful insights from their data securely.

Amazon SageMaker enables the identification of various types of unprocessed data, including images, text documents, and videos, while also allowing for the addition of meaningful labels and the generation of synthetic data to develop high-quality training datasets for machine learning applications. The platform provides two distinct options, namely Amazon SageMaker Ground Truth Plus and Amazon SageMaker Ground Truth, which grant users the capability to either leverage a professional workforce to oversee and execute data labeling workflows or independently manage their own labeling processes. For those seeking greater autonomy in crafting and handling their personal data labeling workflows, SageMaker Ground Truth serves as an effective solution. This service simplifies the data labeling process and offers flexibility by enabling the use of human annotators through Amazon Mechanical Turk, external vendors, or even your own in-house team, thereby accommodating various project needs and preferences. Ultimately, SageMaker's comprehensive approach to data annotation helps streamline the development of machine learning models, making it an invaluable tool for data scientists and organizations alike.

DPM easyData serves as an advanced engine for data de-identification and spoofing, offering methods such as masking, tokenization, anonymization, pseudonymization, and encryption to safeguard sensitive information. Through its data spoofing techniques, the software effectively substitutes entire data sets or fragments with non-sensitive alternatives, generating fictitious data that serves as a robust protective measure. This solution is tailored for web and application server environments, enabling databases to anonymize and tokenize information while enforcing masking policies for users without proper authorization when accessing sensitive materials. DPM easyData stands out for its precise control, allowing administrators to specify which users are permitted to access certain protection measures and outlining the actions they can perform under these policies. Furthermore, its highly customizable framework accommodates a wide variety of data types, offering unparalleled flexibility in defining input and token formats to meet diverse security needs. This adaptability ensures that organizations can maintain stringent data protection standards while managing sensitive information effectively.

Multi-cloud data security with a single pane of glass Industry's first SaaS access governance solution. Cloud is fragmented and data is scattered across different systems. Sensitive data is difficult to access and control due to limited visibility. Complex data onboarding hinders data scientist productivity. Data governance across services can be manual and fragmented. It can be time-consuming to securely move data to the cloud. Maximize visibility and assess the risk of sensitive data distributed across multiple cloud service providers. One system that enables you to manage multiple cloud services' data policies in a single place. Support RTBF, GDPR and other compliance requests across multiple cloud service providers. Securely move data to the cloud and enable Apache Ranger compliance policies. It is easier and quicker to transform sensitive data across multiple cloud databases and analytical platforms using one integrated system.

The Solix Enterprise Data Management Suite (Solix EDMS) consolidates all necessary tools to implement a successful Information Lifecycle Management (ILM) strategy. Accessible through a single web interface, this platform features top-tier solutions for database archiving, test data management, data masking, and application retirement. Solix EDMS aims to manage expenses, enhance the performance and availability of applications, and fulfill compliance requirements. It provides business users universal access to archived data via full-text searches, structured SQL queries, and various forms and reports. Furthermore, Solix EDMS enables users to swiftly pinpoint rarely accessed historical data from production applications and securely transfer it to an archive while maintaining data integrity and access. The system's retention management feature ensures that archived data remains stored for a specified duration and can be deleted automatically or manually once it complies with the data retention policy. With these capabilities, organizations can streamline their data management processes effectively.

Create a versatile and centrally coordinated layered defense system to protect against insider threats using the premier Privileged Access Management platform available. The Single Connect™ Privileged Access Management Suite stands out as the quickest to implement and the most secure PAM solution, enhancing both IT security and operational efficiency for enterprises and telecommunications companies worldwide. With Single Connect™, IT managers and network administrators can effectively safeguard access, manage configurations, and maintain comprehensive records of all activities within the data center or network infrastructure, recognizing that any compromise in privileged account access could significantly disrupt business operations. This platform offers an array of tools, capabilities, and reliable log records, along with audit trails, to assist organizations in meeting various regulatory requirements, such as ISO 27001, ISO 31000: 2009, KVKK, PCI DSS, EPDK, SOX, HIPAA, and GDPR, especially in highly regulated sectors like finance, energy, healthcare, and telecommunications. By implementing Single Connect™, businesses can not only enhance their security posture but also ensure compliance with critical industry regulations.

Adaptive is a robust data security platform aimed at safeguarding sensitive data from exposure across both human and automated entities. It features a secure control plane that allows for the protection and access of data, utilizing an agentless architecture that does not demand any network reconfiguration, making it suitable for deployment in both cloud environments and on-premises settings. This platform empowers organizations to grant privileged access to their data sources without the need to share actual credentials, thereby significantly bolstering their security stance. Additionally, it supports just-in-time access to an array of data sources such as databases, cloud infrastructure, data warehouses, and web services. Furthermore, Adaptive streamlines non-human data access by linking third-party tools or ETL pipelines through a unified interface, while ensuring data source credentials remain secure. To further reduce the risk of data exposure, the platform incorporates data masking and tokenization techniques for users with non-privileged access, all while maintaining existing access workflows. Moreover, it ensures thorough audibility by providing identity-based audit trails that cover all resources, enhancing accountability and oversight in data management practices. This combination of features positions Adaptive as a leader in the realm of data security solutions.

Our focus is on ensuring that data is secure and effortlessly accessible for businesses. The Safe Haven platform enhances customer intelligence, facilitates large-scale engagement, and fosters innovative opportunities for business expansion. Designed for the contemporary enterprise, our platform grants comprehensive control over data access and usage through top-tier software solutions for identity management, activation, and data collaboration. You can harness data access to uncover valuable business insights and boost revenue, all while keeping strict oversight of how data is used. Effectively connect with your target audiences across various channels, platforms, publishers, or networks, while securely converting data between identity realms to enhance outcomes. Safeguard your customer information using cutting-edge privacy-preserving technologies and sophisticated methods that limit data movement, yet still allow for the generation of insights. In doing so, you empower businesses to thrive in a data-driven landscape while upholding the highest standards of data protection.