Enterprise Compliance for Architecture AI

The Challenge: AI in Enterprise Architecture

Architecture teams adopting AI face governance questions that traditional documentation tools haven't addressed:

How do you track who accessed proprietary designs when an architect asks AI to summarize a system specification?
How do you maintain audit trails when AI retrieves information from multiple technical documents?
How do you retain AI conversation logs that discuss sensitive system architectures?
How do you respond to compliance requests for access logs?

Dhamaka provides the data governance controls and audit evidence your compliance team needs.

Data Governance Controls

Access Logging

Every AI interaction with technical documentation is logged in a tamper-evident audit trail that records:

Who accessed the information
What was accessed (design documents, specifications, technical standards)
When the access occurred
Context for the access (project, team, conversation)
Outcome of the interaction

Integrity and Authenticity

Compliance teams and auditors expect access logs to be authentic and unaltered. Dhamaka uses cryptographic chaining to ensure audit records cannot be modified without detection. Any alteration to historical records breaks the chain and is immediately detectable, providing assurance that logs presented to auditors accurately reflect what occurred.

Access Controls

Dhamaka implements user identification tied to all AI interactions:

Every team member has a unique identifier tied to their AI queries
Organization and project-based access controls limit which technical documentation each user can query

Transmission Security

All data transmission between clients and Dhamaka is encrypted using TLS (Transport Layer Security). Cloudflare enforces TLS on all connections, supporting TLS 1.2 and 1.3.

Data Lifecycle Management

Retention Periods

Configure retention aligned with your enterprise requirements:

Organization-level defaults for standard retention
Project-specific overrides for sensitive or regulated systems
Automatic archival before deletion
Legal hold capability to preserve records during disputes

Knowledge Management

Dhamaka supports appropriate data lifecycle management for architectural knowledge:

Retention policies can be configured per project
Active projects can have longer retention than archived work
All deletions are permanently documented

Implementation Checklist

Configure organization-level retention policies
Set up project-level overrides where requirements differ
Define legal hold procedures for IP disputes and investigations
Train architecture team on appropriate AI use with sensitive documentation
Establish audit log review schedule
Document AI data governance in enterprise architecture guidelines