Alternatives to Private AI

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.

Accountable can supercharge your risk management and empower your team. Simplify the process of managing risk across all levels of your organization, become compliant with HIPAA, GDPR, CCPA and more privacy laws, and build trust with your customers and partners. Get a snapshot of your compliance in real-time with our intuitive dashboards Monitor and track employees as they take their requiredd Security Awareness trainings through our online video courses. Determine potential risks and address compliance shortcomings through our guided security risk and data impact assessments. We will provide all the required privacy and security policies for your organization. Send and manage vendor contracts such as Business Associate Agreements and Data Processing Agreements through our vendor center. Share compliance, security, and privacy reports with those inside and outside your organization who need a high level view of your risk management program.

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.

Differential privacy, a mathematically proven standard for data privacy, ensures that all data can be used to perform analytics and machine learning without compromising individual records. LeapYear's differentially secure system protects some the most sensitive datasets around the globe, including financial transactions, medical information, social media data, and medical information. The system protects all information about individuals, entities, transactions, and businesses, and allows data scientists, analysts, and researchers to derive value from all data. Traditional methods, such as anonymization, aggregation or masking data value, can be easily used to reconstruct sensitive information. LeapYear's differential privacy implementation provides mathematically supported assurances that individual records cannot be reconstructed while allowing all data to be used for reporting.

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.

Syntho is typically deployed in the trusted and safe environment of our clients, so that (sensitive data) never leaves this environment. Our connectors are ready-to-use to connect you to the target environment and source data. Syntho supports 20+ database connectors, 5+ filesystems, and can connect to every leading database and filesystem. Define what type of synthetizations you want to run. Mask or synthesize values realistically. Automatically detect sensitive data types. Use and share protected data in a secure manner, while maintaining compliance and privacy.

Start with developers to create a culture and infrastructure that respects privacy and security. This will ensure that PII is prioritized and protected throughout your organization. The Piiano Vault can be deployed to create a secure, centralized PII zone that is only accessible to you in your cloud environment. This will prevent data breaches and ensure privacy best practices are being applied. For unparalleled access visibility, you can control all PII interactions using advanced policy controls, encryption, tokenization, and a privacy-centric scanner. To comply with GDPR, CCPA, and other privacy regulations, centralize data to implement privacy-by design, pseudonymization (RTBF), and data subject access requests.

Store, anonymize mask, mine, redact and share sensitive data securely with 100% accuracy and complete international data privacy compliance. You can save time and money by separating PII from other data. Embed PII Vault into your innovative solutions to reduce time to market and deliver the most PII-secure solutions available. Unlock data for more accurate and targeted messages. All data can be anonymized in one simple step before it reaches the platform. Once anonymized, Poly- Anonymization™ allows you to combine disparate anonymous data sets on an individual basis without receiving any PII. Replace PII by a compliant, multi-valued, non-identifying key that is used to link anonymous data from multiple organizations.

Tonic automatically creates mock datasets that preserve key characteristics of secure data sets so that data scientists, developers, and salespeople can work efficiently without revealing their identities. Tonic creates safe, de-identified data from your production data. Tonic models your production data from your production data to help tell a similar story in your testing environments. Safe and useful data that is scaled to match your real-world data. Safely share data across businesses, teams, and borders to create data that is identical to your production data. PII/PHI identification and obfuscation. Protect your sensitive data by proactive protection with automatic scanning, alerts and de-identification. Advanced subsetting across diverse database types. Fully automated collaboration, compliance, and data workflows.

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.

PieEye simplifies complex processes of managing user consent, and compliance with privacy laws such as GDPR, CPRA/CCPA. This is the fastest, easiest, most efficient and automated solution for any size ecommerce company. Our platform will get you up-and-running in minutes, without the need to do headstands or spend weeks or months on tedious compliance tasks. PieEye is easy to install, easy to automate and allows you streamline your compliance efforts. Discover how easy compliance can be. Cookie compliance is now more important than ever, with more laws governing data privacy. Our cutting-edge Cookie Banner makes your website fully comply with all regulations. It protects your customers' rights to privacy and you. Our automated platform streamlines your entire process and allows you to manage requests easily while ensuring compliance with all relevant laws.

Operationalize data pipelines using privacy-centric data management tools. Truata Calibrate empowers businesses to make data useful while leveraging privacy as an important commercial differentiator. Our cloud-native, frictionless software allows businesses to quickly operationalize privacy-compliant pipelines, so that teams can work with the data responsibly and confidently. Truata Calibrate, powered by intelligent automation and a centralized dashboard, facilitates rapid and effective risk assessment and mitigation. The platform offers a smart and standardized solution to manage privacy risks, and ensures data can be transformed effectively for safe use across your business ecosystem. Before performing forensically-targeted de-identification, you can access dynamic recommendations for data transform and view privacy-utility impacts simulations. Transform data into privacy-enhanced datasets which can be shared, transferred and used responsibly.

NMTY Enterprise protects all privacy-sensitive data in your organization, whether it is stored on databases or files. NMTY Enterprise can be integrated into your IT environment to anonymize data sources. NMTY Enterprise allows you to anonymize data, regardless of the format it is stored in. This includes databases and individual files. Anonymize data in a database, or in files such as CSV or XML. Data is anonymized at the source. This prevents duplicates of non-anonymized information. The connections to your data sources are encrypted and support integrated authentication. It is possible to directly anonymize images and documents. Our solutions are based on the most recent innovations and can be integrated directly into your processes. We can always expect the best results.

Privacy1 infrastructure brings transparency, safeguards GDPR | CCPA compliance, builds trust for your business. The solution shields your data centric organizations, lower data leak risks, ensures that no personal data is processed except with the right permission. The service has built in rich features you need to meet data compliance requirements and enforce your organizational data security to the highest level

Privacy Analytics offers data anonymization software and services for healthcare and consumer organizations. Privacy Analytics allows you to safely and responsibly use your sensitive data assets for innovation that benefits all. Privacy Analytics allows you to safely de-identify your health data to the highest standards while still preserving its utility. The regulatory deadlines are becoming more stringent. Data requests are becoming more urgent. There is greater pressure to maintain your company's reputation than ever before. The climate surrounding data privacy continues to get more intense. Everybody, from regulators to consumers, is holding organizations accountable. Drug makers are under increasing pressure to disclose clinical data and documents. As the pressure mounts, so does the demand for privacy. Solutions that maximize transparency while protecting the privacy of trial participants are needed.

PK Protect is a platform for data protection that helps organizations protect sensitive information in a variety of environments. It offers robust tools for data discovery and classification, encryption and monitoring. This ensures that critical data will be protected at rest and during transit. PK Protect's automated policies and compliance controls help businesses meet regulatory requirements such as GDPR and HIPAA, while minimizing data breach risks. The platform integrates into various systems, allowing for a unified management of data security across cloud environments, on-premises environments, and hybrid ones. PK Protect offers real-time visibility, proactive threat detection and helps organizations reduce security vulnerabilities.

Subsalt is a platform that allows anonymous data to be used at enterprise scale. Subsalt’s Query Engine dynamically optimizes tradeoffs between data security and fidelity to source data. The queries return fully-synthetic results that preserve row-level granularity, data formats and data formats. Subsalt offers compliance guarantees backed by third-party audits which satisfy HIPAA’s Expert Determination Standard. Subsalt offers multiple deployment models that can be tailored to the privacy and security needs of each client. Subsalt is HIPAA and SOC2-Type 2-compliant. The system is designed to minimize any risk of data exposure or breach. Subsalt's Postgres compatible SQL interface integrates directly with existing data and ML software, making adoption a breeze.

Our platform allows businesses to use data, including its application in advanced analysis, machine learning and AI, to do great things without worrying that customers, employees or intellectual property are at risk. The Protegrity Data Protection Platform does more than just protect data. It also classifies and discovers data, while protecting it. It is impossible to protect data you don't already know about. Our platform first categorizes data, allowing users the ability to classify the type of data that is most commonly in the public domain. Once those classifications are established, the platform uses machine learning algorithms to find that type of data. The platform uses classification and discovery to find the data that must be protected. The platform protects data behind many operational systems that are essential to business operations. It also provides privacy options such as tokenizing, encryption, and privacy methods.

IBM InfoSphere®, Optim™, Data Privacy offers extensive capabilities to mask sensitive data in non-production environments such as development, testing, QA, or training. This single offering offers a variety transformation techniques that can replace sensitive information with fully functional, functionally masked data. Substrings, arithmetic, sequential or random number generation, date ageing, and concatenation are all examples of masking techniques. The context-aware masking capabilities allow data to be retained in a similar format as the original. Apply a range of masking techniques on-demand to transform personally-identifying information and confidential corporate data in applications, databases and reports. Data masking tools can be used to prevent misuse of information. They allow you to mask, obfuscate, and privatize personal information that is distributed across non-production environments.

Describe your data model at an abstract level using XML. It is not necessary to have developer skills. Use a variety of function libraries to create realistic data. Write your own extensions using Javascript or Java. Integrate your data processing into Gitlab CI, Jenkins or Jenkins. Benerator's model driven data toolkit allows you to generate, anonymize and migrate data. Define processes for anonymizing or pseudonymizing data in plain XML without needing developer skills. Protect your customers' privacy and stay GDPR compliant. Mask and obfuscate data sensitive for BI, testing, development or training. Subsetting allows you to combine data from different sources while maintaining data integrity. Transform and migrate your data in multisystem landscapes. Reuse your test data models for migration to production environments. In a microsystems architecture, keep your data consistent and reliable.

Databunker is a lightning-fast, open-source vault developed in Go for secure storage of sensitive personal records. Protect user records from SQL and GraphQL injections with a simple API. Streamline GDPR, HIPAA, ISO 27001, and SOC2 compliance. Databunker is a special secure storage system designed to protect: - Personally Identifiable Information (PII) - Protected Health Information (PHI) - Payment Card Industry (PCI) data - Know Your Customer (KYC) records Databunker introduces a new approach to customer data protection: - Secure Indexing: Utilizes hash-based indexing for all search indexes - No Clear Text Storage: Ensures all information is encrypted, enhancing overall security - Restricted Bulk Retrieval: Bulk retrieval is disabled by default, adding an extra layer of defense - API-Based Communication: Backend interacts with Databunker through API calls, similar to NoSQL solutions - Record Token: Databunker creates a secured version of your data object - an object UUID token that is safe to use in your database

Privacy engineering tools delivered as APIs. In minutes, you can synthesize and transform data. Trust your users and the community. Gretel's APIs allow you to instantly create anonymized or synthetic data sets so that you can safely work with data while protecting your privacy. Access to data must be faster in order to keep up with the development pace. Gretel's data privacy tools bypass blockers, and allow for Machine Learning and AI applications to access data faster. Gretel Cloud runners makes it easy to scale up your workloads to the cloud or keep your data safe by running Gretel containers within your own environment. Developers will find it much easier to train and create synthetic data using our cloud GPUs. Scale workloads instantly with no infrastructure required. Invite colleagues to collaborate on cloud projects, and share data between teams.

Businesses today face severe punishment if they fail to meet the ever-increasing privacy standards of regulators and the general public. Vendors must keep up with the latest algorithms to protect sensitive data like PII or PHI. HushHush is at the forefront in privacy protection (Patents US9886593, US20150324607A1, US10339341) thanks to its PII data discovery tool workbench (also known data de-identification software, data masking software, and obfuscation program). It allows you to find sensitive data about your customers and classify it. You can also anonymize it and comply with GDPR and GLBA requirements. To create comprehensive and secure data anonymization solutions, you can use a variety of rule-based atomic addition anonymization components. HushHush components can be used to anonymize both direct identifiers (SSNs, credit cards names, addresses, telephone numbers, etc.). Both fixed and variable algorithms are available for indirect identifiers.

Overcome challenges when acquiring data to train AI and machine learning systems. Rendered.ai, a PaaS, is designed for data scientists and engineers. Create synthetic datasets to train and validate ML/AI. Experiment with scene content, sensor models, and post-processing. Catalogue and characterize real and synthetic datasets. Download or move data into your own cloud repositories to be processed and trained. Synthetic data can be used to boost innovation and productivity. Create custom pipelines for modeling diverse sensors and computer-vision inputs. Python sample code is available for free and can be customized to model SAR, RGB Satellite imagery, and other sensor types. Flexible licensing allows for almost unlimited content creation. Create labeled, high-performance computing content quickly in a hosted environment. No-code configuration allows data scientists and engineers to collaborate.

When capturing data in real-life situations is difficult, we create diverse, fully-labeled image datasets. Our procedural technology provides the highest-quality, unbiased, and labeled synthetic datasets to improve your computer vision model. AI Verse gives users full control over scene parameters. This allows you to fine-tune environments for unlimited image creation, giving you a competitive edge in computer vision development.

MakerSuite simplifies this process. MakerSuite allows you to easily tune custom models, iterate on prompts and augment your data with synthetic data. MakerSuite allows you to export your prompts as code in your favorite languages, such as Python and Node.js, when you are ready to move on to code.

Synthesized can help you unlock the full potential of your data projects and AI. We automate all stages of data preparation and provisioning with cutting-edge AI. The platform synthesizes data without exposing personal information or causing compliance issues. Software to prepare and provide accurate synthetic data for building better models at scale. Synthesized solves the problem of data sharing for businesses. 40% of companies that invest in AI can't report business benefits. Our easy-to-use platform allows data scientists, product, and marketing teams to focus on revealing critical insight. Without representative data, testing data-driven applications can be difficult. This can lead to problems when services go live.

A platform for ML engineers that provides synthetic data to facilitate the development of better AI models. Simple APIs allow for the instant generation of photorealistic, well-labeled images. Cloud-based generation platform that is highly scalable delivers millions of perfectly labeled photos. On-demand data allows for new data-centric approaches to create more efficient models. A broader range of pixel-perfect labels, including segmentation maps and dense 2D/3D landmarks as well as depth maps, surface norms, depth maps, and more, is now available. You can quickly design, test, refine, and revise your products before you build hardware. To optimize your system, prototype different imaging modalities, camera placements, lens types, and other lens types. Your models will be less biased if there are misbalanced data sets. Privacy will still be protected. Equal representation across identities, facial attributes and poses, as well as lighting and camera settings. We have worked with top-notch customers in many different use cases.

Public video data collection is becoming more risky due to the increasing capabilities of facial recognition technology. Brighter AI's Precision Blur allows for the most precise face redaction in the world. Deep Natural Anonymization, a privacy solution that uses generative AI, is unique. It creates synthetic facial overlays to protect individuals against recognition while maintaining data quality for machine-learning. You can use the Selective Redaction user interface to anonymize specific information in videos. Some use cases, such as media or law enforcement, do not require all faces to be blurred. After the automatic detections, it is possible to (de)select individual objects. Our Analytics Endpoint provides relevant metadata such as the original objects' bounding box locations, facial landmarks, and person attributes. You can retrieve relevant information using JSON outputs, while also having compliant, anonymized photos or videos.

Privacy engineering is a new field that intersects with data engineering and information security. It also has intersections in software development, privacy law, and software development. Its goal is ensuring that personal data are stored and processed in the most legal way possible, while respecting and protecting the privacy of those individuals to whom the data belongs. Security engineering is a prerequisite for privacy engineering, but it's also a separate discipline that aims at ensuring the safe processing and storage sensitive data. Privacy & Security Engineering is required if your organization processes sensitive or personal data (or both). This is particularly true if you are doing your own data science or engineering.

Protect, Monitor, and Discover enterprise sensitive data across multiple platforms and environments. Automate your subject rights response and demonstrate regulatory compliance - all in one solution

Unlike most data management systems, PHEMI Health DataLab is built with Privacy-by-Design principles, not as an add-on. This means privacy and data governance are built-in from the ground up, providing you with distinct advantages: Lets analysts work with data without breaching privacy guidelines Includes a comprehensive, extensible library of de-identification algorithms to hide, mask, truncate, group, and anonymize data. Creates dataset-specific or system-wide pseudonyms enabling linking and sharing of data without risking data leakage. Collects audit logs concerning not only what changes were made to the PHEMI system, but also data access patterns. Automatically generates human and machine-readable de- identification reports to meet your enterprise governance risk and compliance guidelines. Rather than a policy per data access point, PHEMI gives you the advantage of one central policy for all access patterns, whether Spark, ODBC, REST, export, and more

With the most comprehensive range of products, you can implement privacy compliance and data security in Salesforce. A thorough data inventory and risk assessment are essential for privacy programs to be successful. Most organizations overlook data or struggle with spreadsheets and manual processes. Our Personal Data Inventory product automates and streamlines DPIA and enterprise data inventories flows. Your organization will be able to easily have a clear risk assessment and a data inventory. Many organizations are experiencing an increase in privacy rights requests. It is difficult, inconsistent, and error-prone to respond to these requests manually, increasing the risk of non-compliance. Our Privacy Rights Automation product allows self-service and automates all privacy related activities. A standardised and error-free solution to reduce the risk of non-compliance

The Synthetic Data vault (SDV) was designed as a Python library that allows you to create tabular synthetic data. The SDV uses machine learning algorithms to emulate patterns in synthetic data. The SDV offers a variety of models, from classical statistical methods to deep learning methods. Create data for single tables or multiple connected tables. Compare the synthetic data with the real data using a variety measures. Diagnose problems and create a quality report for more insights. Control data processing to enhance the quality of synthetic information, choose different types of anonymization and define business rules as logical constraints. Use synthetic data to replace real data or as an enhancement. The SDV is a comprehensive ecosystem of synthetic data models, metrics, and benchmarks.

Easy to use, integrate and anonymize faces, license plate numbers, vehicles and bodies. Solve privacy issues for a variety of commercial and industrial applications. Our products and expertise are trusted by global industry leaders. We solve anonymization challenges so you can concentrate on your core business. Our team is there to help you along your privacy journey. Data protection is our core business. That's why we have put in place strong measures to comply with GDPR and other data privacy laws. Our cloud service will handle all processing on our infrastructure. You can also use Docker containers to deploy the container on-premises or in your private/public clouds. You will be charged per video or image hour. You can create a free demo account to test it. Blur faces, license plate numbers, persons, and vehicles in images with a simple call to REST.

With automated data quality profiling, and synthetic data generation, adopting data-centric AI is easier than ever. We help data scientists unlock the full potential of data. YData Fabric enables users to easily manage and understand data assets, synthetic data, for fast data access and pipelines, for iterative, scalable and iterative flows. Better data and more reliable models delivered on a large scale. Automated data profiling to simplify and speed up exploratory data analysis. Upload and connect your datasets using an easy-to-configure interface. Synthetic data can be generated that mimics real data's statistical properties and behavior. By replacing real data with synthetic data, you can enhance your datasets and improve your models' efficiency. Pipelines can be used to refine and improve processes, consume data, clean it up, transform your data and improve its quality.

syntheticAIdata will help you create diverse datasets at scale and with ease. Our solution is not only a cost-saving tool, but also ensures privacy, regulatory compliance and accelerates the journey of your AI products to market. Let syntheticAIdata transform your AI aspirations to achievements. Synthetic data can be generated in large quantities and cover a wide range of scenarios when real data are not available. Automatically generated annotations include a variety of options. This reduces the time required for data collection and tagging. Generating synthetic data at a large-scale will reduce costs for data collection, tagging and data storage. Our user-friendly, no-code solution allows even those with little technical knowledge to generate synthetic data. Our solution is the easiest to use in the market, with seamless integration via one-click with leading cloud platforms.

Rockfish Data is a synthetic data generation platform that unlocks the true value of operational information. Rockfish Data helps enterprises use siloed datasets to train ML/AI, create compelling datasets for demos, and much more. The platform intelligently adjusts and optimizes diverse data sets, seamlessly adapting to different data types, sources and structures, for maximum efficiency. It is designed to deliver specific, measurable business results, while ensuring data integrity and privacy. Rockfish's operationalization of synthetic data allows organizations to overcome data-silos, enhance machine-learning and artificial intelligence workflows and generate high quality datasets for different applications.

Accelerate data processing tasks such as structuring, labeling and preprocessing. Manage all your data on a central platform that is easy to integrate. Increase data accessibility quickly with privacy-protected synthetic data and user friendly exchange platforms. The Aindo platform for synthetic data allows you to securely share data between departments, with external providers, partners and the artificial-intelligence community. Synthetic data exchange and collaboration can help you discover new synergies. Securely and openly acquire missing data. Your clients and stakeholders will appreciate the comfort and trust you provide. Aindo's synthetic data platform eliminates data inaccuracies, implicit bias and provides fair and complete insights. Enhance information to make databases resilient to special events. Balance datasets which misrepresent the true population to get a fair and accurate depiction. Fill in data gaps with precision and accuracy.

OneView creates next-generation virtual synthetic datasets for ML algorithm training. We provide ready-to-use datasets for all objects in any environment, with a focus on satellite and aerial imagery. VSD is computer-generated, real-like imagery. It can be used to replace real imagery. It is a cost-effective, scalable, and highly accurate training material for ML algorithm. OneView bridges the gap between increasing availability of earth observation data, and the limited ability to use it for intelligence gathering. We provide the tools to improve data analysis and enable geospatial imagery to yield new and valuable insights. It doesn't matter if you have long-tail or rare objects, or if you don't have enough data. We can generate a dataset for every object. We can generate any environment. High-detailed, customized environment for model training.

Syntheticus®, a data exchange platform, overcomes limitations such as scarcity and bias in data, while enabling data exchange at scale. Our synthetic data platform allows you to generate high-quality, compliant data samples that are tailored to your business goals and analytics needs. Synthetic data allows you to tap into a variety of high-quality resources that aren't always available in real life. You can conduct more reliable research by using high-quality data that is consistent. This will lead to better products, business decisions, and services. You can accelerate product development cycles by having reliable, fast data at your fingertips. Synthetic data is designed as a private and secure data source by default. This protects sensitive data and maintains compliance with privacy laws.

We can no longer rely upon real-life conversations as physical customer interactions shift to digital. Customers communicate their intentions and share their needs using data. Data is a key tool for understanding customers and testing our assumptions. Privacy regulations like GDPR and CCPA make deep understanding more difficult. This gap in customer understanding is bridged by the MOSTLY AI synthetic dataset platform. Businesses can benefit from a reliable, high-quality generator of synthetic data in many different applications. The story doesn't end there. MOSTLY AI's synthetic dataset platform is more versatile than any other synthetic data generator. MOSTLY AI's versatility makes it an indispensable tool for software development and testing. From AI training to explainability and bias mitigation, governance to realistic test data, with subsetting, referential integrity.

Enterprise synthetic test data solutions. It is essential that test data accurately reflects the structure of your database or application. This means it must be easy for you to model and maintain each project. Respect the referential integrity of parent/child/sibling relations across data domains within an app database or across multiple databases used for multiple applications. Ensure consistency and integrity of synthetic attributes across applications, data sources, and targets. A customer name must match the same customer ID across multiple transactions simulated by real-time synthetic information generation. Customers need to quickly and accurately build their data model for a test project. GenRocket offers ten methods to set up your data model. XTS, DDL, Scratchpad, Presets, XSD, CSV, YAML, JSON, Spark Schema, Salesforce.

Amazon SageMaker lets you identify raw data, such as images, text files and videos. You can also add descriptive labels to generate synthetic data and create high-quality training data sets to support your machine learning (ML). SageMaker has two options: Amazon SageMaker Ground Truth Plus or Amazon SageMaker Ground Truth. These options allow you to either use an expert workforce or create and manage your data labeling workflows. data labeling. SageMaker GroundTruth allows you to manage and create your data labeling workflows. SageMaker Ground Truth, a data labeling tool, makes data labeling simple. It also allows you to use human annotators via Amazon Mechanical Turk or third-party providers.

Create high-fidelity 3D environments and diverse synthetic data quickly and easily to improve model performance. Bifrost is the fastest and easiest way to create high-quality synthetic images to improve ML performance. By avoiding time-consuming and expensive real-world data collection, you can prototype and test up 30x faster. Generating data to account rare scenarios that are underrepresented in the real data will result in more balanced datasets. Manual annotation and labeling can be resource-intensive and prone to errors. Quickly and easily generate data that are pre-labeled, pixel-perfect. Real-world data can inherit biases from the conditions under which it was collected and generate data that solves for these instances.

Synthetic data is the key to a leading-edge technology that allows for flawless retail execution. Vision technology for consumer packaged products. Choose from a catalog of over 100,000 SKUs on the Neurolabs platform, including top brands like P&G, Nestle Unilever, Coca-Cola and more. Our API will automatically stitch together multiple shelf images uploaded by your field agents from their mobile devices. SKU-level detection gives you detailed information that can be used to calculate retail execution KPIs, such as out-of shelf rate, shelf share percentage and competitor price comparison. Discover how our cutting edge image recognition technology can maximize store operations, improve customer experience, and boost profits. Implement a real deployment in less than a week. Access image recognition datasets covering over 100,000 SKUs.

Data is a valuable business asset. With the right AI model it is possible to use data in order to build and understand customers profiles, identify trends, and identify potential new business opportunities. It takes a lot of data to build accurate and robust AIs, which is a challenge from both a quality and quantity perspective. Stringent regulations, including GDPR, also restrict the use and sharing of sensitive data like customer data. It's time to change the way we do things. It's time for a new approach, especially in a software test environment where it is difficult to access good quality testing data. We often see actual customer data used, which can lead to GDPR non-compliance with heavy financial penalties. Artificial Intelligence is expected to increase productivity in businesses by at least 40%, but businesses struggle to deploy AI solutions or fully unlock them due to data-related issues. ADA generates artificial data using advanced deep-learning.

You can anonymize license plates and faces in your data without worrying about non-compliance to privacy laws like GDPR, CCPA and APPI. Compare the images before and afterwards using our examples. Upload a JPEG image or PNG to test our model. See how our model anonymizes all personal information markers. The solution for GDPR Compliance offers several key features. It can be customized to meet specific requirements and ensure GDPR compliance. We provide the best deployment options to reduce processing time and human intervention. This saves both time and money. There are a variety of deployment options, including cloud, API, and on-premise. The solution blurs faces and license plates even in difficult vision conditions.

RNDGen Random Data Generator, a user-friendly tool to generate test data, is free. The data creator customizes an existing data model to create a mock table structure that meets your needs. Random Data Generator is also known as dummy data, csv, sql, or mock data. Data Generator by RNDGen lets you create dummy data that is representative of real-world scenarios. You can choose from a variety of fake data fields, including name, email address, zip code, location and more. You can customize generated dummy information to meet your needs. With just a few mouse clicks, you can generate thousands of fake rows of data in different formats including CSV SQL, JSON XML Excel.

We have made significant progress serving the AI value-chain through projects that span different data types, industries and geographical locations. Our diverse experience allows us to address unique challenges, and optimize solutions in different sectors. Custom data sources with high precision for your model needs, from around the globe, that are in strict compliance with GDPR and ISO standards. Data annotation and labeling is performed with 95% accuracy for all data types. This ensures flawless model performance. In the early stages, determine your model's performance to receive an expert opinion that is unbiased on critical performance measures like bias, duplication and ground truth response. Validate the output of your model by leveraging the validation team's expertise to optimize and improve accuracy.