Alternatives to AnalyticDiD

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.

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.

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.

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.

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.

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.

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.

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.

iDox.ai Suite is an AI-powered document protection platform built for organizations that need to redact, anonymize, compare, and manage sensitive information across large volumes of files. The software automatically detects personal, health, financial, business, and regulated data so teams can remove or obscure confidential content before documents are shared. iDox.ai Suite supports PDFs, scanned files, spreadsheets, and other document formats commonly used in compliance-heavy environments. It can identify and redact PII, PHI, financial details, signatures, logos, confidential business information, and other sensitive content. The platform is designed for legal teams, government agencies, healthcare organizations, life sciences companies, and enterprises that manage privacy-sensitive files. Its data anonymization capabilities help organizations prepare documents for analysis, collaboration, disclosure, regulatory submission, or AI system use without exposing protected information. Document comparison features help teams review changes and verify content differences more efficiently. Compliance reporting tools generate audit-ready documentation that supports internal governance, FOIA processes, legal review, and regulatory obligations. iDox.ai Suite helps organizations improve document security, speed up review cycles, and maintain stronger control over sensitive data.

Privacy Analytics specializes in providing cutting-edge data anonymization solutions and software tailored for businesses in the consumer and healthcare sectors. Our services empower you to harness your sensitive data assets securely and ethically, fostering innovation that serves the greater good. With Privacy Analytics, you can effectively de-identify health data to meet the highest standards while maintaining its practical value. As regulatory requirements become increasingly stringent, the timelines for data requests are also shrinking, placing added pressure on organizations to maintain their reputations. The ongoing climate of data privacy is becoming more critical, with consumers and regulators alike holding companies accountable. This heightened scrutiny has amplified the stakes for pharmaceutical companies, necessitating safe disclosures of clinical data and related documents. As the demand for transparency escalates, the challenge of balancing it with the privacy of trial participants becomes even more pronounced, underscoring the need for innovative solutions that ensure both accountability and confidentiality in data handling. Consequently, organizations must adapt swiftly to these evolving expectations to thrive in this challenging environment.

Organizations must stay abreast of the constantly evolving privacy environment while safeguarding personally identifiable information they handle. PK Privacy equips these organizations with the ability to automate processes for data discovery and reporting, thereby alleviating some of the operational challenges associated with privacy regulations. This solution streamlines the DSAR response process, enabling compliance to be achieved more efficiently and within budget constraints. Additionally, it allows for the establishment of rules to automatically delete or redact sensitive information as soon as it is identified. The platform facilitates pseudonymization, anonymization, and de-identification of private personal data, ensuring enhanced protection. Furthermore, it identifies data that may legally require archiving or deletion based on its age or inactivity. Organizations can also detect and verify breaches through ongoing monitoring, while accurately assessing and reporting the resultant impact of such incidents. By providing continuous oversight of endpoints, servers, and enterprise solutions, PK Privacy ensures that organizations can effectively manage their privacy data and maintain compliance. Ultimately, embracing these automated solutions not only simplifies privacy management but also strengthens overall data security.

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.

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.

You can forget about manual content classification or data entry. Doculayer.ai provides a configurable workflow that includes document processing services such as OCR, document type classification and topic classification, as well data extraction and masking. Doculayer.ai allows business users to take control of their learning and training by providing an intuitive user interface that makes labeling documents and data easy. Our hybrid data extraction approach allows machine learning models to be combined with patterns, rules, and library scripts to produce better results in less time. Data masking is an option to anonymize or pseudonymize sensitive data in documents. Doculayer.ai provides document intelligence to your Content Services Platform and Business Process Management systems. Your existing IT environment can be augmented for document processing by machine learning, natural language processing and computer vision technologies.

Subsalt represents a groundbreaking platform specifically designed to facilitate the utilization of anonymous data on a large enterprise scale. Its advanced Query Engine intelligently balances the necessary trade-offs between maintaining data privacy and ensuring fidelity to original data. The result of queries is fully-synthetic information that retains row-level granularity and adheres to original data formats, thereby avoiding any disruptive transformations. Additionally, Subsalt guarantees compliance through third-party audits, aligning with HIPAA's Expert Determination standard. It accommodates various deployment models tailored to the distinct privacy and security needs of each client, ensuring versatility. With certifications for SOC2-Type 2 and HIPAA compliance, Subsalt has been architected to significantly reduce the risk of real data exposure or breaches. Furthermore, its seamless integration with existing data and machine learning tools through a Postgres-compatible SQL interface simplifies the adoption process for new users, enhancing overall operational efficiency. This innovative approach positions Subsalt as a leader in the realm of data privacy and synthetic data generation.

BizDataX offers a data masking solution that delivers test data with the quality comparable to that of production environments. It ensures adherence to GDPR and various other regulations by concealing customer identities while supplying data for developers and testers. Utilizing masked or anonymized data rather than actual production data significantly mitigates associated risks. The focus is placed on managing policies, fulfilling business requirements, governing sensitive data, and adhering to diverse regulations. It also facilitates the monitoring of databases, data sources, and tables to identify the locations of sensitive information. Furthermore, it allows for the management of extensive customer databases and the seamless exchange of data with online partner retailers and delivery services. Given the stringent regulations surrounding medical records, compliance can be effectively maintained through the process of data anonymization, ensuring that patient information is protected. This capability not only safeguards sensitive data but also enhances the overall data management strategy for organizations.

Discover the advantages of utilizing a Trusted Third Party (TTP) for the meticulous pseudonymization of personal data, enabling you to conduct data analysis while adhering to GDPR regulations. Our fundamental offering revolves around the pseudonymization of personal data, utilizing techniques that ensure irreversible pseudonyms and the enhancement of behavioral data. The pseudonymized dataset serves as the foundation for subsequent processing by our clients. Additionally, our filtering service allows for the proportional sharing of personal data, ensuring privacy is maintained throughout the process. We carefully filter information through a rigorously managed pseudonymized whitelist, guaranteeing that only data pertaining to individuals on this list is shared. Viacryp also provides expert privacy consultation focused on the safeguarding and security of personal data. In collaboration with our partners, we offer guidance on the necessary measures organizations should implement to meet GDPR compliance, addressing both technical solutions and organizational protocols. By prioritizing these compliance strategies, businesses can enhance their data protection practices effectively.

Naix is an innovative tool powered by AI that specializes in the anonymization and redaction of documents, effectively eliminating personally identifiable information in a fast, precise, and secure manner. Utilizing advanced techniques such as machine learning, natural language processing, and linguistic modeling, it is capable of identifying a wide range of sensitive data, including company names, legal forms, personal names, locations, email addresses, URLs, dates, identification numbers, images, and financial figures. This versatile tool is compatible with various file formats, including PDFs, Word and Excel documents, emails, scanned files, and images, and offers support for multiple languages, specifically English, German, and French. Naix streamlines the majority of the anonymization process while also providing manual redaction options to address any exceptions that may arise. Additionally, users can implement predefined pseudonyms to maintain context when complete anonymization is not feasible. The user-friendly interface guides individuals seamlessly from the initial document upload through to the review of findings and the generation of a secure output file, ensuring an efficient workflow throughout the process. Overall, Naix represents a comprehensive solution for organizations seeking to protect sensitive information while maintaining operational integrity.

Accelerate your data processing with ease, collaborate in a secure environment, and uncover fresh insights effortlessly. Our software is fully compliant with HIPAA regulations and provides robust security and privacy measures. You can experiment with various components to tailor the solution to your specific business needs while ensuring compliance is maintained. The platform automatically tracks and generates all necessary documentation, simplifying the management of compliance reporting. By utilizing de-identified data, companies can unearth unique insights and drive innovative business strategies. Nevertheless, the safe handling of de-identified data necessitates expert certifications, which are currently performed by consultants often lacking in transparency, speed, and adaptability. Integral offers an automated expert certification solution that allows you to engage with your data in mere hours instead of the typical months required. This transformative approach not only streamlines the certification process but also enhances overall efficiency in data management.

On-demand patient identity resolution is achieved by efficiently mastering and connecting data in real-time. By converting protected health information into universal, de-identified HealthVerity IDs, organizations within the life sciences sector can effectively construct and disseminate the patient journey across various partner datasets, thereby establishing a unified source of truth regarding patient identity. This approach also facilitates internal data sharing among different organizational departments, enhancing the overall understanding of the patient journey. Furthermore, it allows for adaptable external data exchanges with entities such as patient registries, health insurers, and other associated companies. HealthVerity Census serves as an initial step toward developing a data strategy focused on activation, interoperability, and the longitudinal tracking of patient information. Utilizing an advanced PaaS de-identification solution, it empowers the activation of both internal and external data touchpoints, breaking down silos that often isolate critical information within the enterprise. These comprehensive capabilities ultimately contribute to improved patient outcomes and more informed decision-making across the healthcare landscape.

IRI DarkShield uses several search techniques to find, and multiple data masking functions to de-identify, sensitive data in semi- and unstructured data sources enterprise-wide. You can use the search results to provide, remove, or fix PII simultaneously or separately to comply with GDPR data portability and erasure provisions. DarkShield jobs are configured, logged, and run from IRI Workbench or a restful RPC (web services) API to encrypt, redact, blur, etc., the PII it discovers in: * NoSQL & RDBs * PDFs * Parquet * JSON, XML & CSV * Excel & Word * BMP, DICOM, GIF, JPG & TIFF using pattern or dictionary matches, fuzzy search, named entity recognition, path filters, or image area bounding boxes. DarkShield search data can display in its own interactive dashboard, or in SIEM software analytic and visualization platforms like Datadog or Splunk ES. A Splunk Adaptive Response Framework or Phantom Playbook can also act on it. IRI DarkShield is a breakthrough in unstructured data hiding technology, speed, usability and affordability. DarkShield consolidates, multi-threads, the search, extraction and remediation of PII in multiple formats and folders on your network and in the cloud, on Windows, Linux, and macOS.

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

Clario’s Image Redact AI efficiently removes sensitive patient identifiers from various media formats, including videos, photos, and PDFs. This cutting-edge solution combines AI-powered de-identification with the vigilant oversight of a skilled quality control (QC) team, ensuring compliance with EU GDPR and other privacy laws. By implementing this technology, organizations can mitigate the risk of significant penalties and potential liabilities stemming from data breaches. Each image undergoes a thorough de-identification process, leveraging our unique AI capabilities alongside comprehensive human visual QC review to confirm that all necessary redactions have been executed. Additionally, all images are securely stored across multiple geographical locations in data centers that conform to the latest security standards and practices. Users can effortlessly access and evaluate their protected videos, photos, and PDFs on any device, making it an invaluable resource for clinical trial research projects, while also enhancing overall data security and accessibility.

IRI Data Masking as a Service is a professional services engagement to secure PII. Step 1: IRI agrees under NDA terms to classify, analyze, and report on the sensitive, at-risk data in your sources. We will discuss an initial cost estimate then hone it with you during data discovery. Step 2: Transfer the unprotected data to a secure on-premise or cloud-based staging area or provide remote, supervised access to IRI to the data sources(s) at issue. We'll use the tools in the award-winning IRI Data Protector suite to mask that data according to your business rules, on an ad hoc or recurring basis. Step 3: Our experts can also move newly-masked data to incremental replicas in production or to lower non-production environments. From either, the data is now safe for analytic initiatives, development, testing, or training. Tell us if you need additional services, like re-ID risk scoring (expert determination) of the de-identified data. This approach provides the benefits of proven data masking solution technology and services without the need to learn and customize new software from scratch. If you do want to use the software in-house, you will have everything pre-configured for easier long-term self-use and modification.

The Soflab G.A.L.L. application aims to anonymize sensitive information in non-production settings, facilitating the creation of high-quality synthetic data that mirrors real datasets, thus enabling effective testing processes. As it safeguards sensitive details, the application effectively mitigates the risk of data leaks. By substituting genuine data with artificial counterparts, it reduces the potential for data breaches while identifying sensitive or erroneous entries. This results in decreased legal and financial risks while ensuring the protection of customer transactional data. The application promotes a unified approach to anonymization across various non-production systems, thus maintaining a consistent data model and preserving connections with production data. Additionally, synthetic data generated from essential production attributes retains statistical integrity for business intelligence and artificial intelligence applications. A centralized test data repository allows for controlled data reuse, which not only lowers maintenance expenses and accelerates deployment timelines—up to five days—but also facilitates simulation and reusable scenarios effectively. Overall, the application enhances testing efficiency while prioritizing data security.

DataVantage provides a wide range of data management solutions that focus on the protection and governance of sensitive information in both mainframe and distributed settings. Among its key products are DataVantage for IMS, Db2, and VSAM, which incorporate sophisticated features for data masking, editing, and extraction, ensuring the safeguarding of Personally Identifiable Information (PII) during non-production activities. Furthermore, DataVantage DME (Data Masking Express) enables economical, real-time data masking for Db2, IMS, and VSAM environments, facilitating compliance without hindering existing operations. For distributed infrastructures, DataVantage Global offers comprehensive data masking, obfuscation, and de-identification processes, promoting both compliance and operational effectiveness across various platforms. Moreover, DataVantage Adviser streamlines the management of COBOL files following mainframe rehosting or application modernization, thereby improving data accessibility and editing capabilities. This holistic approach to data management not only enhances security measures but also supports organizations in their quest for regulatory compliance and operational integrity.

Streamlining privacy through automated secure redaction for document sharing is the cornerstone of Rectify's approach. By utilizing privacy-centric artificial intelligence, Rectify efficiently eliminates sensitive information during the data sharing process. This innovation significantly reduces the need for human intervention in identifying and expunging consumer identities, trade secrets, intellectual property, and other confidential data from datasets destined for third-party distribution. Our team has safeguarded tens of millions of pages, and the number continues to rise. With our advanced "privacy-enabled AI" for deidentification, organizations can move away from tedious manual redaction processes. The risks associated with disclosing sensitive information without a reliable redaction tool can be severe, making it imperative to choose an effective redaction service. Rectify offers a comprehensive solution tailored to your redaction requirements, ensuring your business's security and privacy are maintained at all times. By opting for Rectify's secure redaction, you can automate privacy protection and foster confidence in your data handling practices.

Libelle DataMasking (LDM) is a powerful, enterprise-level solution designed for the automated anonymization of sensitive personal information, including names, addresses, dates, emails, IBANs, and credit card details, converting them into realistic substitutes that preserve logical consistency and referential integrity across both SAP and non-SAP environments such as Oracle, SQL Server, IBM DB2, MySQL, PostgreSQL, SAP HANA, flat files, and cloud databases. With the capability to handle up to 200,000 entries per second and facilitate parallel masking for extensive datasets, LDM employs a multithreaded architecture, ensuring efficient reading, anonymization, and writing of data with exceptional performance. The solution boasts over 40 predefined anonymization algorithms—including those for numbers, alphanumeric characters, date shifting, and various forms of masking for names, emails, IBANs, and credit cards—along with tailored templates specifically designed for SAP modules like CRM, ERP, FI/CO, HCM, SD, and SRM. Additionally, its scalability and flexibility make it suitable for organizations of all sizes looking to enhance their data security measures.

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

DevOps can be simplified and privacy concerns eliminated by giving your teams full data autonomy via an easy-to use self-service portal. You can simplify access, remove data roadblocks, and speed up provisioning for data analysts, dev, testing, and other purposes. The Accelario Continuous DataOps platform is your one-stop-shop to all of your data needs. Eliminate DevOps bottlenecks, and give your teams high-quality, privacy-compliant information. The platform's four modules can be used as standalone solutions or as part of a comprehensive DataOps management platform. Existing data provisioning systems can't keep pace with agile requirements for continuous, independent access and privacy-compliant data in autonomous environments. With a single-stop-shop that provides comprehensive, high-quality, self-provisioning privacy compliant data, teams can meet agile requirements for frequent deliveries.

iDox.ai Guardrail serves as an immediate security measure for AI applications, designed to safeguard sensitive information from being exposed during generative AI tasks. This innovative solution functions at the endpoint, intercepting user prompts, uploaded files, and any AI interactions prior to data transmission from the device. Guardrail employs policy-driven mechanisms to identify and prevent the leakage of sensitive information, including personally identifiable information (PII), protected health information (PHI), payment card information (PCI), intellectual property, and other confidential business data. In contrast to conventional data loss prevention (DLP) systems, Guardrail is tailored specifically for AI applications. It continuously observes user engagement with AI platforms like ChatGPT, Microsoft Copilot, and Claude, applying protective measures in real-time to ensure security. Among its key features are: - Continuous monitoring of prompts and file submissions - Detection of sensitive data with AI awareness - Real-time anonymization and sanitization processes - Defense against risks associated with AI agents, such as unauthorized file access incidents (e.g., OpenClaw) - Implementation of website whitelisting and strict policy enforcement. Additionally, Guardrail enhances user confidence in utilizing AI technologies while ensuring compliance with data privacy regulations.

Salesforce Privacy Center provides businesses with a comprehensive solution for managing data privacy and ensuring compliance with regulations like GDPR. The platform helps organizations safeguard sensitive data by allowing for easy de-identification or deletion of unnecessary information in production systems. It supports streamlined data subject access requests (DSARs), making it easier to retrieve and deliver relevant customer data in compliance with privacy laws. Privacy Center also simplifies the management of customer consent through the Preference Manager, which allows businesses to create customizable no-code forms to capture consent for marketing, data sharing, and more. By consolidating customer privacy requests and enhancing data governance, Privacy Center helps businesses mitigate risks, build trust with customers, and stay prepared for applications like Agentforce and Salesforce's Customer 360.

Occlira effectively eliminates personal and sensitive information from legal documentation prior to sharing or utilizing external AI services, while also enabling the restoration of that information afterward. The software is capable of analyzing .docx and .pdf formats, identifying various elements such as names, addresses, email addresses, phone numbers, identification and tax numbers, IBANs, case identifiers, and corporate names through a localized machine learning model that is specifically optimized for the German, Austrian, and Swiss contexts. All operations are conducted on the user’s device, ensuring that documents are not transmitted to any external servers. Recognized entities are substituted with uniform placeholders like [PERSON_1] or [COMPANY_A], which maintains the readability of the text. The mapping of detected data is securely stored on the device, allowing for a reversible process: users can anonymize a contract, utilize it with AI models like ChatGPT or Claude, and then seamlessly reintegrate the actual names into the document afterward. Each detection is presented for user verification prior to implementation, and the formatting of the output remains true to the original document. This solution is available as a signed desktop application compatible with both Windows and macOS, offered under a one-time licensing model. Additionally, users benefit from enhanced privacy, knowing their data is protected throughout the entire process.

LexisNexis Health Equity and Inclusion Insights offers an extensive and actionable dataset focused on the social determinants of health (SDoH) at the individual level. This valuable information empowers healthcare organizations to enhance population health, advance clinical research, and pursue initiatives aimed at promoting health equity. By highlighting obstacles to care, the solution aids in refining care delivery and fostering more equitable healthcare choices, alongside developing diverse clinical research programs. It supplies de-identified datasets that can be integrated with other such datasets through LexisNexis Gravitas, a tokenization tool that utilizes a referential data layer for accurately matching de-identified records from various sources. Achieving health equity hinges on the ability to pinpoint health barriers and predictors of adverse health outcomes, allowing for targeted interventions that can positively impact individual patients. Ultimately, this focus on precision and actionable insights can lead to improved health outcomes across entire communities.

The Astracore Biobanking System serves multiple functions, including the management of biological samples, research activities, and any scenario that necessitates a hierarchical, transaction-based approach to storage management and analysis. This biobank can act as any type of repository or bio-repository, facilitating the storage, tracking, and management of various samples, whether they need to be kept at low temperatures or at room temperature. The system accommodates different storage mediums, which can encompass both physical and virtual samples. Additionally, it allows for the storage of participant personal data in various formats, including fully identifiable, pseudonymous, or de-identified information. Access to the system can be limited to specific users through the implementation of security profiles, ensuring sensitive data remains protected. Featuring an intuitive, hierarchical, and normalized structure, the system supports multi-level storage management that can be easily configured through drag-and-drop functionality. A 2D visualization tool is also provided, enabling users to see detailed information about storage availability, highlighting both vacant and occupied slots. Ultimately, the storage utilized can be a combination of local, remote, physical, or virtual resources, offering flexibility to meet diverse biobanking needs. This adaptability ensures that the Astracore Biobanking System can effectively support a wide range of research and sample management requirements.

Renowned startpoint security software products in the IRI Data Protector suite and IRI Voracity data management platform will: classify, find, and mask personally identifiable information (PII) and other "data at risk" in almost every enterprise data source and sillo today, on-premise or in the cloud. Each IRI data masking tool in the suite -- FieldShield, DarkShield or CellShield EE -- can help you comply (and prove compliance) with the CCPA, CIPSEA, FERPA, HIPAA/HITECH, PCI DSS, and SOC2 in the US, and international data privacy laws like the GDPR, KVKK, LGPD, LOPD, PDPA, PIPEDA and POPI. Co-located and compatible IRI tooling in Voracity, including IRI RowGen, can also synthesize test data from scratch, and produce referentially correct (and optionally masked) database subsets. IRI and its authorized partners around the world can help you implement fit-for-purpose compliance and breach mitigation solutions using these technologies if you need help. ​

We assist developers in addressing critical global challenges by maximizing the potential of sensitive data while minimizing associated risks. This motivation drives us to create privacy-focused tools for machine learning and analytics tailored for the evolving landscape of distributed data. Various forms of data are continuously produced and kept in cloud environments, on-site locations, and increasingly at the network's edge. The financial burden of de-identifying, transferring, centrally storing, and managing vast amounts of data can often be overwhelming. Regulations such as HIPAA, GDPR, PIPEDA, and CCPA impose restrictions on the ways in which data can be aggregated, particularly across different regions. By utilizing federated learning and analytics, we ensure that only model parameters are transmitted from each private server, allowing data custodians to maintain complete control over their information. By leveraging this innovative approach, businesses can enhance their offerings to existing clients through the development of new features that tap into the shared insights derived from customer data. This way, organizations can not only comply with regulations but also drive growth in a secure and efficient manner.

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.

Challenging the conventional data value chain, we offer risk-aware solutions for de-identifying sensitive information, enabling further processing. Whether you prefer on-premises management for complete control or a secure externalized service, FedEHR serves as your all-in-one solution compliant with GDPR and HIPAA regulations. As our world evolves, so does the nature of our data, with an unprecedented surge of IoT devices generating vast amounts of information and reflecting our increasingly interconnected and ubiquitous society. This shift inevitably raises the pressing question of our "quantified self." However, what are the implications and potential risks of data sharing? Who possesses access to this information, and for which purposes? What is the true worth of data, and who holds ownership rights? While this abundant personal and sensitive information presents incredible opportunities for self-discovery, it simultaneously poses significant challenges for societies striving to develop advanced governance frameworks that can responsibly manage this wealth of data. As we navigate these complexities, the importance of transparency and accountability in data management cannot be overstated.

Flatiron Health's Evidence Solutions provide a versatile method for generating real-world evidence, both prospective and retrospective, which aids life sciences companies in efficiently meeting their oncology research objectives. At the heart of these offerings is Flatiron Horizon, a comprehensive platform that combines a rich database of more than 5 million anonymized patient records and 1.5 billion data points, coupled with advanced curation techniques and disease-specific machine learning models. This innovative platform is designed to facilitate various phases of the biopharma lifecycle, including discovery, clinical study design, regulatory submissions, and post-marketing commitments. Furthermore, Flatiron's services deliver customized real-world data configurations that cater specifically to oncology, enabling prospective evidence generation through minimally invasive studies and optimizing protocols for better patient identification. Additionally, the platform ensures a streamlined transfer of data from electronic health records to electronic data capture systems with the functionality of Flatiron Clinical Pipe, enhancing overall research efficiency and effectiveness. Such capabilities position Flatiron Health as a leader in transforming oncology research through the power of real-world data.

Assign a distinctive identification number to each specimen while gathering pertinent clinical information. Organize specimens according to participants, protocols, departments, investigators, institutions, disease sites, anatomical locations, and other relevant categories. Segment samples into new specimens that receive new unique IDs along with their corresponding data. Ensure the tracking of each specimen from the point of collection through freezing, thawing, and eventual disposal. Maintain compliance with HIPAA regulations, allowing for data de-identification where necessary. Oversee various biospecimen repositories simultaneously. Collect specimens in accordance with protocol calendar timepoints or through a single event timepoint, as required. Additionally, keep track of and upload consent forms and other necessary documents. Create a freezer and storage container configuration that accurately reflects physical storage conditions. Generate multiple customizable reports for inventory management, quality assurance, consent documentation, manifest creation and tracking, invoice management, and more. The system should allow users to efficiently query the specimen repository for specific types of samples, enhancing usability and accessibility. Furthermore, ensure that all data is accurately recorded and easily retrievable to facilitate ongoing research and analysis.

Azure Health Data Services represents a collection of specialized technologies designed for managing protected health information (PHI) in a cloud environment. This service is founded on widely accepted global standards such as Fast Healthcare Interoperability Resources (FHIR)® and Digital Imaging Communications in Medicine (DICOM). It ensures the protection of data privacy while adhering to compliance regulations, allows for the de-identification of data to facilitate secondary uses, and enables the generation of valuable insights through analytics and AI capabilities. As an upgraded version of the Azure API for FHIR, it introduces enhanced technologies and services. Current users can maintain their experience without any service interruptions or modifications to pricing. By unifying healthcare data within the cloud, it simplifies the exchange of PHI throughout the entire care continuum. Additionally, it standardizes a variety of data sources, including clinical, imaging, device, and unstructured data, by utilizing FHIR, DICOM, and MedTech services, thereby enhancing interoperability and efficiency in healthcare delivery. This comprehensive approach aims to improve patient outcomes and streamline healthcare operations.

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.

KIProtect creates innovative software solutions designed to enable secure, legally compliant, and privacy-conscious handling of sensitive personal data. As concerns surrounding data security and protection continue to grow, these critical aspects are frequently overlooked due to the complexities and time demands of technical data safeguards. Our mission is to transform this landscape! Through our open-source offerings, we empower businesses to implement advanced anonymization and pseudonymization methods, ensuring optimal protection of their data throughout the processing stages. This approach not only enhances security but also fosters greater trust between companies and their customers.

Wayfinder serves as a comprehensive SaaS platform designed for big data in the healthcare and life sciences sectors, seamlessly integrating data, analytics, and AI processes to expedite the extraction of insights essential for these industries. This innovative solution enables quicker access to detailed insights derived from healthcare data. Utilizing the robust Databricks Lakehouse framework, Wayfinder provides connectivity to over 45 terabytes of de-identified and enhanced claims data, designed to cater to the specific data handling and processing demands of the healthcare and life sciences sectors at a large scale. By leveraging Wayfinder, users can scrutinize high-quality claims data to pinpoint rare patient populations, target healthcare providers effectively, construct detailed patient journeys, and uncover significant market trends, all while providing the granular detail necessary to inform strategies that foster differentiation and growth. With Wayfinder, the focus shifts from data preparation and management to in-depth analysis, empowering stakeholders to make informed decisions and drive innovation in their practices. This platform not only enhances efficiency but also positions users to leverage data more strategically for future advancements.