How does elDoc support a resilient security and AI governance framework?

elDoc combines enterprise document security, AI governance, access control, and Human-in-the-Loop (HITL) oversight to protect sensitive information throughout the document and AI lifecycle.

The framework is built around several key areas:

  1. Platform Security & Resilience: elDoc supports different deployment architectures, including Cloud, Hybrid, On-Premise, and high-availability configurations, enabling organizations to align availability, redundancy, failover, and infrastructure design with their operational requirements.

  2. Identity & Authentication: Access can be protected through enterprise authentication mechanisms including MFA, OTP, SSO, and Active Directory integration, helping ensure that only authenticated users can access the platform.

  3. Roles & Granular Permissions: Role-based and granular access controls determine who can access documents and what actions they can perform. Permissions can extend across hierarchical folder structures and control actions such as reading, editing, deleting, copying, downloading, uploading, printing, sharing, and managing permissions.

  4. Encryption & Data Protection: elDoc supports protection of sensitive information through encryption and controlled data access, including protection of data at rest and in transit. Private deployment architectures can also keep documents, AI processing, vector data, and LLM workloads within organization-controlled infrastructure.

  5. Document-Level Security: Organizations can apply controls including secure sharing, OTP and password protection, expiration dates, watermarks, download restrictions, version history, and audit trails to maintain control over sensitive documents throughout their lifecycle.

  6. AI Governance & Controlled AI Access: AI Agents and Agentic RAG operate within established user access permissions. AI does not provide a user with unrestricted access to enterprise knowledge simply because the information has been indexed—the user can interact only with content they are authorized to access.

  7. Human-in-the-Loop (HITL): AI decisions do not have to be accepted automatically. elDoc supports confidence thresholds, human validation, review, and approval workflows, allowing organizations to introduce human oversight where accuracy, risk, compliance, or business rules require it.

  8. AI & LLM Control: With its LLM-agnostic architecture, elDoc allows organizations to select AI models and deployment configurations according to their security and governance policies. Multiple LLMs can operate within the platform for different use cases, including private or locally deployed models where required.

  9. Auditability & Accountability: Audit trails, document histories, version control, AI task history, and sharing activity provide greater visibility into how enterprise information is accessed, modified, shared, and processed.

Together, these controls help organizations implement AI and document automation while maintaining security, governance, human oversight, data sovereignty, and organizational control.

How does elDoc ensure encryption and data protection?

elDoc utilizes MongoDB (a NoSQL database) built to efficiently handle large datasets with a dynamic schema. MongoDB provides robust encryption features, ensuring data protection in transit, at rest, and in use, safeguarding sensitive information throughout its entire lifecycle. 

  1. Encryption in transit: Encryption in transit secures data during transmission between clients and servers, preventing unauthorized access or tampering. In MongoDB Atlas, all network traffic to MongoDB clusters is protected by Transport Layer Security (TLS), which is enabled by default and cannot be disabled. The default version is TLS 1.2. Data transmitted to and between MongoDB cluster nodes is encrypted in transit using TLS, ensuring secure communication throughout. 
  2. Encryption at rest: Encryption at rest ensures that all stored files and data are encrypted, providing a critical layer of database-level protection. In MongoDB Atlas, customer data is automatically encrypted at rest using AES-256 to protect all volume (disk) data. This process utilizes your cloud provider's transparent disk encryption, with the provider managing the encryption keys. Additionally, you have the option to enable database-level encryption, allowing you to use your own encryption keys via AWS Key Management Service (KMS), Google Cloud KMS, or Azure Key Vault. 
  3. In-Use Encryption: Encryption in use secures data while it's being processed. Data is encrypted on the client side using customer-controlled keys before it's sent to, stored in, or retrieved from the database. The benefits of this approach are: 1) Comprehensive data protection: Data is encrypted throughout its entire lifecycle, whether in use, during backups, at rest, or in transit. 2) Compliance assurance: Helps meet strict data privacy requirements such as GDPR, HIPAA, PCI DSS, and more.

For the latest information, please visit MongoDB.