Audit Data Architecture

Executive Summary

Audit Data Architecture defines how Algosure stores and governs audit data. Audit data records material actions, decisions, access, approvals, events, AIOS activity, integrations, document actions, security decisions, and administrative changes.

Why This Exists

Algosure must explain who did what, when, under which tenant and organization, with what authority, and what result. Audit data supports accountability, security investigation, compliance readiness, AI explainability, and dispute resolution.

Owner

The owner is the Chief Product Officer and Enterprise Architect.

Business Value

Audit data makes Algosure trustworthy, reviewable, supportable, and enterprise-ready.

Audit Data Flow

flowchart LR
    Action[Material Action or Decision]
    Context[Tenant, Organization, User, Entitlement Context]
    Event[Domain / Application / Integration Event]
    Audit[(Audit Data)]
    Review[Audit Review]

    Action --> Context
    Context --> Event
    Event --> Audit
    Audit --> Review

Audit Data Sources

Source	Audit Data
APIs	Requests, denials, approvals, high-impact commands, sensitive reads.
Domains	Lifecycle transitions, source fact changes, policy decisions, approval state.
Events and outbox	Publication, consumption, failure, retry, dead-letter, replay attempt.
AIOS	Tool calls, context access, reasoning, generated outputs, confidence, approvals.
Documents	Upload, view, download, generate, sign, share, delete, retention action.
Integrations	External calls, callbacks, credentials used, provider response, failures.
Security	Authentication, authorization, entitlement, MFA, suspicious access, tenant access changes.
Administration	Feature flags, policy changes, support actions, audit review, platform configuration.

Audit Data Rules

Rule	Requirement
Audit data is tenant-scoped	Audit records for customer data carry TenantId and OrganizationId where applicable.
Audit data is protected	Audit access requires privileged authorization, tenant context, and reason for access.
Audit data is not a dumping ground	Audit records should capture material traceability without storing raw secrets or unnecessary payloads.
Audit data supports correlation	CorrelationId and CausationId connect audit records to requests, events, workflows, and AIOS work.
Audit data retention is governed	Retention must reflect legal, customer, security, and operational requirements.
Audit data is tamper-resistant by design	Audit records should be protected from unauthorized modification or deletion.

Non-Implementation Boundary

This document does not define audit table schemas, storage products, retention periods, SIEM integrations, or log pipeline implementation.