About Caber Systems

Caber helps enterprises secure and govern their generative AI applications by observing and controlling how AI agents and users interact with data. The platform fingerprints data across various sources, including APIs, datastores, and models, to provide granular intelligence, remove duplication, and enforce security policies. By integrating with enterprise IAM systems, Caber traces data lineage and enables redaction, blocking, and auditing of data across all LLM interactions.

```xml <problem> Enterprises lack visibility and control over how generative AI applications interact with sensitive data, leading to potential data leaks, compliance violations, and security risks. Existing data loss prevention (DLP) and data classification technologies struggle to handle the variable-sized data chunks and lack of policy context inherent in AI agent interactions. This makes it difficult to ensure data confidentiality, integrity, and availability when using AI. </problem> <solution> Caber provides a data governance platform that enables enterprises to secure and govern their generative AI applications by observing and controlling how AI agents and users interact with data. The platform fingerprints data across various sources, including APIs, datastores, and models, to provide granular intelligence and enforce security policies. By integrating with enterprise IAM systems, Caber traces data lineage and enables redaction, blocking, and auditing of data across all LLM interactions. This allows organizations to maintain control over data access and usage within AI environments, mitigating risks associated with agentic AI. </solution> <features> - Data fingerprinting across APIs, datastores, and models for granular data intelligence. - Integration with enterprise IAM systems for user identity and access control. - Data lineage tracking to understand the flow of data through AI applications. - Data redaction and blocking capabilities to prevent unauthorized data access. - Auditing of data interactions to ensure compliance with data governance policies. - Real-time monitoring of data-in-transit to AI agents. - Policy enforcement based on user identity and data context. </features> <target_audience> Caber is designed for enterprise technology leaders, CISOs, and data governance teams who need to secure and control data usage within generative AI applications. </target_audience> ```

What does Caber Systems do?

Where is Caber Systems located?

Caber Systems is based in Menlo Park, United States.

When was Caber Systems founded?

Caber Systems was founded in 2022.

Location

Menlo Park, United States

Founded

2022

Employees

2 employees

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Caber Systems

Score: 13/100

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Executive Summary

caber.com 100+

Founded 2022 – Menlo Park, United States

Funding

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Team (<5)

Dave Brace

aiPM entrepreneur

Company Description

Problem

Enterprises lack visibility and control over how generative AI applications interact with sensitive data, leading to potential data leaks, compliance violations, and security risks. Existing data loss prevention (DLP) and data classification technologies struggle to handle the variable-sized data chunks and lack of policy context inherent in AI agent interactions. This makes it difficult to ensure data confidentiality, integrity, and availability when using AI.

Solution

Caber provides a data governance platform that enables enterprises to secure and govern their generative AI applications by observing and controlling how AI agents and users interact with data. The platform fingerprints data across various sources, including APIs, datastores, and models, to provide granular intelligence and enforce security policies. By integrating with enterprise IAM systems, Caber traces data lineage and enables redaction, blocking, and auditing of data across all LLM interactions. This allows organizations to maintain control over data access and usage within AI environments, mitigating risks associated with agentic AI.

Features

Data fingerprinting across APIs, datastores, and models for granular data intelligence.

Integration with enterprise IAM systems for user identity and access control.

Data lineage tracking to understand the flow of data through AI applications.

Data redaction and blocking capabilities to prevent unauthorized data access.

Auditing of data interactions to ensure compliance with data governance policies.

Real-time monitoring of data-in-transit to AI agents.

Policy enforcement based on user identity and data context.

Target Audience

Caber is designed for enterprise technology leaders, CISOs, and data governance teams who need to secure and control data usage within generative AI applications.