Daxa provides application-centric guardrails for Generative AI, enabling organizations to implement robust data access controls and governance measures directly within their AI applications. This approach mitigates risks of unauthorized data access and ensures compliance with privacy regulations, allowing businesses to leverage their data securely and responsibly.
Funding
$3.7M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Generative AI applications often lack sufficient data access controls, leading to risks of unauthorized data access, data leaks, and compliance violations when using sensitive company information. Existing data governance solutions are often difficult for developers to implement directly within AI applications, slowing down deployment and increasing security risks.
Solution
Daxa provides application-centric guardrails for Generative AI, enabling organizations to implement robust data access controls and governance measures directly within their AI applications. By integrating directly into development frameworks like LangChain and LlamaIndex, Daxa allows developers to embed data controls with minimal code changes. Daxa offers features such as data access control, a Data Bill of Materials for data transparency, AI application security with a Zero Trust architecture, and AI governance tools to ensure compliance with privacy regulations. This approach mitigates risks of unauthorized data access and ensures compliance with privacy regulations, allowing businesses to leverage their data securely and responsibly.
Target Audience
Primary customers are developers and security teams building and deploying Generative AI applications within organizations that require robust data security and compliance.
Features
- Data Access Control: Ensures sensitive information remains off-limits to unauthorized users by extending existing data access privileges to AI applications.
- Data Bill of Materials: Provides full transparency into the data flowing through AI applications, including attributes, classifications, and origins.
- AI App Security: Implements a Zero Trust architecture with built-in monitoring, tracking, and auditing to protect AI applications from insider threats and data poisoning.
- AI Governance: Helps organizations stay aligned with privacy and compliance regulations by preventing bias and managing ethical risks.
- Application-Centric Guardrails: Enables developers to weave data controls directly into their applications, regardless of the framework used (e.g., LangChain, LlamaIndex).
- Data lineage: Provides visibility into the source, entitlements, and semantics of data used in AI applications.