Data Architecture

Executive Summary

Data Architecture defines the logical data architecture for Algosure. PostgreSQL is the primary operational store, Domains own source facts, Analytics owns reporting projections, and Intelligence owns AI memory records without taking ownership of operational facts.

Why This Exists

Algosure operates across customer organizations, procurement workflows, compliance evidence, opportunities, bids, contracts, funding, learning, analytics, AIOS, integrations, documents, events, and audit records. Data architecture must preserve ownership, tenant isolation, classification, retention, and source-of-truth clarity.

Owner

The owner is the Chief Product Officer and Enterprise Architect.

Business Value

Clear data architecture prevents source-of-truth drift, cross-tenant exposure, duplicated operational facts, unmanaged AI memory, and reporting projections becoming accidental business authority.

Data Architecture View

flowchart TB
    Domains[Domain Modules]
    Postgres[(PostgreSQL Core Transactional Database)]
    ReadModels[Read Models]
    Search[(Search Index)]
    Documents[(Document / Object Storage)]
    Vector[(AI Semantic Memory / Vector Store)]
    Audit[(Audit Data)]
    Outbox[(Event / Outbox Data)]
    Analytics[(Analytics Projections)]

    Domains --> Postgres
    Domains --> Outbox
    Domains --> Documents
    Domains --> ReadModels
    ReadModels --> Search
    Domains --> Vector
    Domains --> Audit
    Outbox --> Analytics
    Postgres --> Analytics

Data Store Responsibilities

Data Store	Responsibility
PostgreSQL	Primary operational store for domain-owned transactional data, workflow state, tenant context, event/outbox records, and audit references.
Read models	Query-optimized projections for UI, workflow, API, reporting, and cross-domain read needs.
Document / object storage	Tender packs, compliance evidence, bid documents, contracts, signed documents, exports, generated artifacts, and attachments.
Search index	Searchable projections over approved domain data, documents, opportunities, suppliers, compliance records, and operational knowledge.
AI semantic memory / vector store	Tenant-scoped embeddings, semantic memory records, AIOS context references, and Organizational Memory artifacts governed by Intelligence.
Audit data	Material action, decision, access, event, integration, document, AIOS, and security audit evidence.
Analytics projections	Reporting, KPI, dashboard, trend, and executive insight projections owned by Analytics.

Data Ownership Rules

Rule	Requirement
Domains own source facts	Each Domain owns the operational facts, lifecycle state, and rules for its business concepts.
PostgreSQL is the primary operational store	Operational source facts and transactional state are anchored in PostgreSQL unless an architecture decision approves an exception.
Analytics owns projections only	Analytics owns reporting structures, snapshots, and derived metrics, not source operational facts.
Intelligence owns AI memory records only	Intelligence owns memory metadata, embeddings, reasoning records, and AIOS memory workflows, not source facts from other Domains.
Organization context is mandatory	Tenant and organization context must be carried for customer-scoped data.
Data access follows ownership	Data is accessed through owning modules, governed APIs, events, projections, or approved query boundaries.
Classification and retention apply everywhere	Source facts, documents, search projections, vector memory, audit data, and analytics projections need classification and retention rules.

Non-Implementation Boundary

This document does not define SQL, entity classes, schema names, table structures, indexes, storage buckets, vector database products, search mappings, or retention schedules.