Concentric AI: Data Security Governance Software
Concentric AI helps businesses manage sensitive data and support compliance with regulations like HIPAA and PCI DSS. It is designed for teams that need to monitor data risk across hybrid cloud and on-premises environments.
At a glance
- Category
- Security
- Best for
- Mid-market companies, Enterprise companies, Organizations with hybrid cloud and on-premises data, Regulated industries requiring HIPAA or PCI DSS compliance
- Pricing
- Pricing is usage-based. Semantic Intelligence is priced by the amount of structured and unstructured data scanned, while Semantic DLP is priced by the number of users.
- Key use cases
- Compliance Support, Intellectual Property Protection, GenAI Risk Management, Cloud Data Governance, Unstructured Data Cleanup
- Integrations
- Snowflake, Amazon S3, Microsoft 365, Salesforce, Confluence
- Official website
- concentric.ai
Concentric AI is an agentless, SaaS-based platform designed to discover, categorize, and protect sensitive information. It uses a context-aware AI approach to identify structured and unstructured data, which is intended to be more precise than traditional keyword or regex-based rules.
The platform is built for organizations that handle sensitive data, such as PII, PHI, and intellectual property. It provides visibility into where data is located and who has access, which may help reduce the risk of unauthorized exposure.
Beyond discovery, the platform includes capabilities for Data Security Posture Management (DSPM) and Data Loss Prevention (DLP), specifically addressing risks associated with GenAI tools like Microsoft Copilot, ChatGPT, and Google Gemini. It also supports data deduplication and retention policy enforcement.
Buyers should confirm the platform's integration capabilities with their specific data stores and evaluate how the usage-based pricing model fits their budget based on the volume of data scanned.
Key Features
Uses context-aware AI to find and categorize structured and unstructured data without requiring manual rules or upfront policies.
Assigns labels to business-critical data and can autonomously classify new, semantically similar records.
Identifies and protects data across cloud and on-premises environments to help monitor security posture.
Supports the prevention of data leakage through labeling based on data categorization.
Monitors permissions and access to help prevent overpermissioning and unauthorized data exposure.
Provides visibility and control over sensitive data flowing into AI tools like ChatGPT, Claude, and Microsoft Copilot.
Identifies duplicate data records and helps set data retention policies.
Use Cases
Identifying and protecting PHI and PCI data to support HIPAA and PCI DSS regulatory requirements.
Discovering and securing trade secrets, product designs, and research documents across various data sources.
Monitoring prompt activity and helping prevent sensitive corporate data from being shared with AI tools.
Managing permissions and identifying IAM misconfigurations in environments like Amazon S3.
Finding duplicate files and managing data retention to help organize storage environments.
Best For
Integrations
Pricing
Pricing is usage-based. Semantic Intelligence is priced by the amount of structured and unstructured data scanned, while Semantic DLP is priced by the number of users.
FAQ
It is used to automatically discover, categorize, monitor, and protect sensitive data across cloud and on-premises environments to help reduce risk and support compliance.
The platform is agentless and SaaS-based. It connects to cloud repositories via API and to on-premises repositories using a virtual proxy.
Pricing depends on the product: Semantic Intelligence is based on the volume of data scanned, and Semantic DLP is based on the number of users.
Source category: Security
Source subcategory: Compliance Management
