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29 Listings in Data Privacy Available
What is Tonic.ai? Tonic.ai is test data and synthetic data software offering a platform for de-identifying and synthesizing test data and unstructured data for AI. Founded in 2018 and based in San Francisco, California, USA, Tonic.ai helps engineering and AI teams work more efficiently and achieve better outcomes. Key features of Tonic.ai Database de-identification Synthetic test data Unstructured data redaction (Textual) Subsetting Analytics and reporting Integrations with PostgreSQL, Snowflake, Databricks and more Who uses Tonic.ai? Tonic.ai is built for engineering and AI teams. It suits teams that want database de-identification without spreadsheets and disconnected tools. Why choose Tonic.ai? Compared with alternatives like MOSTLY AI, Tonic.ai differentiates on database de-identification. Pricing is quote-based and scoped to your usage and team size.
Deployment
Compliance
What is Securiti? Securiti is data privacy software offering an AI-powered data command center unifying privacy, security, governance and compliance. Founded in 2019 and based in San Jose, California, USA, Securiti helps enterprises governing data across clouds manage consent, data rights and compliance. Key features of Securiti Sensitive data discovery and classification Privacy and consent management Data access governance AI and data compliance Regulatory compliance (GDPR, CCPA) Integrations, analytics and reporting Who uses Securiti? Securiti is built for enterprises governing data across clouds. It suits teams that want sensitive data discovery and classification without spreadsheets and manual processes. Why choose Securiti? Compared with alternatives like BigID, Securiti differentiates on sensitive data discovery and classification. Pricing is quote-based and scoped to your data footprint and regions.
Deployment
Compliance
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Explore how leading Data Privacy solutions compare based on customer satisfaction, market presence, adoption, and buyer feedback. The Market Grid helps you identify category leaders, high-performing solutions, and emerging products within the Data Privacy ecosystem.
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What is Ethyca? Ethyca is privacy engineering software offering privacy engineering and compliance software with consent, data mapping and DSAR automation. Based in New York, USA, Ethyca helps engineering and privacy teams work more efficiently and achieve better outcomes. Key features of Ethyca Data mapping Consent management DSAR automation Privacy as code Analytics and reporting Integrations with AWS, Snowflake, Stripe and more Who uses Ethyca? Ethyca is built for engineering and privacy teams. It suits teams that want data mapping without spreadsheets and disconnected tools. Why choose Ethyca? Compared with alternatives like Transcend, Ethyca differentiates on data mapping. Pricing is quote-based and scoped to your usage and team size.
Deployment
What is Fasoo? Fasoo is data-centric security software offering data-centric security software for document encryption, DRM and data discovery. Founded in 2000 and based in Seoul, South Korea, Fasoo helps enterprises protecting documents work more efficiently and achieve better outcomes. Key features of Fasoo Enterprise DRM Data discovery Secure document sharing AI data protection Analytics and reporting Integrations with Active Directory, Microsoft 365, AWS and more Who uses Fasoo? Fasoo is built for enterprises protecting documents. It suits teams that want enterprise DRM without spreadsheets and disconnected tools. Why choose Fasoo? Compared with alternatives like Microsoft Purview, Fasoo differentiates on enterprise DRM. Pricing is quote-based and scoped to your usage and team size.
Key Features
Deployment
Compliance
What is Sentra? Sentra is data security posture management software offering data security posture management software that discovers and classifies sensitive cloud data. Based in Israel, Sentra helps cloud security teams work more efficiently and achieve better outcomes. Key features of Sentra Data discovery Classification Posture risk Access governance Analytics and reporting Integrations with Google Tag Manager, WordPress, Shopify and more Who uses Sentra? Sentra is built for cloud security teams. It suits teams that want data discovery without spreadsheets and disconnected tools. Why choose Sentra? Compared with alternatives like Cyera, Sentra differentiates on data discovery. Pricing is quote-based and scoped to your usage and team size.
Key Features
Deployment
Compliance
Data privacy software helps organizations comply with privacy regulations like GDPR and CCPA, managing consent, data subject requests, data mapping, and privacy risk across the data lifecycle. This guide explains what it is, how it works, what matters, and how to choose a platform.
Data privacy software helps organizations comply with privacy regulations like GDPR and CCPA, managing consent, data subject requests, data mapping, and privacy risk across the data lifecycle. This guide explains what it is, how it works, what matters, and how to choose a platform.
Data privacy software (privacy management) helps organizations meet privacy obligations: discovering and mapping personal data, managing consent and preferences, fulfilling data subject access requests (DSARs), assessing privacy risk, and demonstrating compliance.
It is used by privacy, legal, security, and compliance teams to comply with GDPR, CCPA/CPRA, and a growing set of global privacy laws, and to build trust with customers.
The category spans privacy management platforms, consent management (CMP), DSAR automation, and data discovery/mapping tools. Buyers weigh regulation coverage, automation of requests and consent, data discovery accuracy, and integration with their data systems.
The software discovers and maps where personal data lives, captures and honors consent and preferences, automates intake and fulfillment of data subject requests across systems, and runs privacy assessments (PIAs/DPIAs) to manage risk.
Platforms combine data discovery and mapping, consent management, DSAR/request automation, assessment workflows, and reporting, integrated with the systems that hold personal data.
Privacy teams map data and processing, deploy consent capture, automate request handling, run assessments on new processing, and report compliance posture to leadership and regulators.
Find and map personal data across systems to build records of processing and understand exposure.
Capture, store, and honor consent and preferences across web and channels (CMP).
Automate intake, identity verification, data retrieval, and fulfillment of data subject requests.
Run privacy impact assessments on new processing to identify and mitigate risk.
Maintain records of processing activities required by regulations like GDPR.
Dashboards and reports on consent, requests, and privacy posture for audits and regulators.
Meet GDPR, CCPA/CPRA, and other privacy laws with structured, documented processes.
DSAR automation handles requests at scale within legal deadlines instead of manual scrambles.
Proper consent capture and enforcement reduce regulatory and reputational risk.
Discovery and mapping reveal where personal data lives and how it's used.
Demonstrable privacy practices build trust and competitive differentiation.
| Type | Best for | Ideal size | Pros | Limitations |
|---|---|---|---|---|
| Privacy management platforms | End-to-end privacy program | Mid-market to enterprise | Comprehensive | Implementation effort |
| Consent management (CMP) | Consent and preferences | Any | Focused, fast to deploy | Single function |
| DSAR automation | Data subject requests | Any | Automates request workflow | Needs data connections |
| Data discovery & mapping | Find and classify personal data | Any | Foundational visibility | Complements other tools |
SaaS & Technology: Technology companies use data privacy software to scale operations and meet customer, partner, and regulatory expectations as they grow.
Financial Services: Banks, insurers, and fintechs rely on data privacy software for control, auditability, and regulatory compliance.
Healthcare: Healthcare and life-sciences organizations use data privacy software where accuracy, security, and compliance are non-negotiable.
Manufacturing: Manufacturers apply data privacy software across complex, multi-stakeholder processes and supply chains.
Retail & E-commerce: Retailers use data privacy software to manage scale, vendors, and customer-data obligations.
Energy & Utilities: Energy and utility firms use data privacy software to manage heavy regulation, assets, and risk.
Government & Public Sector: Public-sector bodies use data privacy software to meet statutory, transparency, and accountability requirements.
Professional Services: Firms use data privacy software to manage client obligations, risk, and contractual commitments.
Confirm support for the specific laws you're subject to (GDPR, CCPA/CPRA, and others) across your markets.
Assess DSAR and consent automation, manual handling doesn't scale or meet deadlines.
Test how well the tool discovers and maps personal data across your actual systems.
Verify connectors to the systems that hold personal data so requests and mapping work end to end.
Ensure it handles your request volume and data footprint.
Understand pricing by modules, requests, or data sources and how it scales.
AI is improving automated discovery and classification of personal data at scale.
Request fulfillment is becoming more automated across complex data estates.
Privacy, security, and governance are converging into unified data-trust platforms.
Buyers should prioritize regulation coverage, automation depth, discovery accuracy, and integrations over AI alone.
Data privacy software helps organizations comply with privacy regulations by discovering and mapping personal data, managing consent and preferences, automating data subject access requests (DSARs), running privacy assessments, and demonstrating compliance. Used by privacy, legal, security, and compliance teams, it supports laws like GDPR and CCPA/CPRA and helps build customer trust through documented privacy practices.
A data subject access request (DSAR) is an individual's request to access, delete, or otherwise control their personal data, which privacy laws require organizations to fulfill within set deadlines. Privacy software automates intake, identity verification, retrieval of the person's data across connected systems, and fulfillment, making it feasible to meet deadlines at scale rather than handling each request manually.
Most platforms support major laws like the EU's GDPR and California's CCPA/CPRA, and increasingly a broader set of US state and global privacy laws. Coverage varies, so confirm support for the specific regulations in the markets where you operate. Multi-jurisdiction compliance is complex, so prioritize tools that handle the full set of laws you're subject to.
Consent management (often via a consent management platform, or CMP) captures, stores, and enforces individuals' consent and preferences for how their data is used, for example, cookie and tracking consent on websites. It ensures you only process data where you have a valid legal basis and can prove it. Proper consent is foundational to privacy compliance and reducing regulatory risk.
You can't protect or fulfill requests about personal data you don't know you have. Data discovery and mapping reveal where personal data lives across your systems, what categories it includes, and how it's processed, the foundation for records of processing (RoPA), DSAR fulfillment, and risk assessment. Discovery accuracy across your real systems is a key thing to evaluate.
A privacy (or data protection) impact assessment evaluates the privacy risks of a new processing activity, system, or project, and identifies mitigations, and is required under GDPR for high-risk processing. Privacy software provides structured PIA/DPIA workflows so teams assess new initiatives consistently and document the analysis for regulators.
Common models charge by modules (consent, DSAR, assessments, discovery), request volume, data sources, or users, sometimes with implementation fees. Costs scale with your data footprint and request volume. Identify which capabilities you need most and your expected request volume, and clarify how pricing grows as you connect more systems.
Prioritize coverage of the regulations in your markets, automation depth for DSARs and consent, data-discovery accuracy across your real systems, integrations with the systems holding personal data, scalability to your request volume, and pricing. Trial discovery and a real DSAR workflow on your environment, and confirm multi-jurisdiction support if relevant, before committing.
