The administrative layer for the full SiteEngine AI platform
27 years of production heritage, built in Go. Declarative modules, multi-tenant connectors with row-level isolation, a CRUD engine that eliminates admin boilerplate, and a compliance dashboard that treats EU AI Act and US AI framework obligations as first-class concerns. The database is the application - one backup restores everything.
Still running on the same architecture principles 27 years on.
Configure AI experts, trigger document ingestion, monitor citations, and manage Efficiency Engine settings from one admin interface - across all pipeline components and all tenants. How the pipeline works →
SiteEngine has been running without architectural replacement for 27 years - originally Classic ASP (1998), now built in Go. The architecture documented in the SiteEngine thesis is the same architecture that has served live workloads since the year Internet Explorer was still a competitive browser.
The database-as-truth principle has been the foundation since day one: the database is the application. Templates, configuration, content and permissions all live in PostgreSQL. One backup captures the entire system state. No filesystem dependencies. No configuration drift.
The longest-running SiteEngine deployment demonstrates the platform's production stability and longevity.
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management-issues.com - powered by SiteEngine since 2003.
Every aspect of SiteEngine Dashboard - content, configuration, templates, permissions, module state - lives in PostgreSQL. No filesystem dependencies. No configuration drift.
Restore a single backup and the entire site runs. Templates, assets, config - everything is in the database.
Database transactions ensure consistency. No partial deploys, no orphaned files, no configuration drift between environments.
One backup, one restore. No file syncs, no artifact registries, no multi-step recovery procedures.
Enable or disable with a single CLI command. Always-on modules handle core infrastructure; optional modules add capabilities when you need them.
Structured editing, version history, reusable blocks and template assignment. Editorial workflows with draft and released states.
File uploads with image optimisation. Local, MinIO, or Cloudflare R2 backends. Dual-storage pattern for redundancy.
User management, role-based access control, permission matrices and profile management. OAuth integration built in.
Wire SiteEngine AI into the information management platform. Manage experts, trigger ingestion, test conversations and monitor citations from the admin panel.
Product catalogue, inventory and pricing. Enable only when needed - stays off by default to keep the system lean.
Multi-tenancy with hierarchical connectors. Row-level data isolation, cross-connector permissions and audit logging.
The CRUD engine generates complete admin interfaces from declarative configuration. In internal testing, a 25-field entity that takes ~16 hours to build manually requires ~1 hour with CRUD config. List views, edit forms, search, pagination, validation and access control - all from field definitions.
Auto-generated interfaces
List views, edit forms, detail pages and search from field definitions. Inline editing from list views.
Rich field types
Text, richtext, number, date, boolean, media, relation, JSON, computed. Validation rules: required, min/max, pattern, unique.
Version history
Automatic change tracking with diff views. Bulk operations for multi-select actions.
All generated from declarative field definitions. You write config. The engine writes the rest.
Corporate (parent)
Full access across all children
Brand A
Row-level isolation within brand scope
Brand B
Cannot see Brand A data
Connector boundaries are enforced at the query layer. Audit logs track all cross-connector operations.
Connectors are the core isolation unit - each represents a tenant, brand, or site. All tenants share the same application instance and database, with strict row-level data isolation enforced at the query layer.
A SiteEngine differentiator since the early 2000s. Every template variable passes through three phases - giving you powerful content transformation without custom code.
PreProcess
Transform data before rendering - date formatting, URL encoding, string manipulation.
Normal
Standard variable substitution with the processed value into the template output.
PostProcess
Transform rendered output - truncation, HTML stripping, conditional wrapping.
curl -fsSL https://get.siteengine.dev | bash siteengine init --docker siteengine serve # Enable AI module siteengine module enable ai siteengine config ai
Supports Go install, Homebrew, Docker images and systemd for production.
Server filesystem. Best for development and single-server deployments.
S3-compatible, self-hosted. For on-premises and air-gapped environments.
S3-compatible with zero egress fees. Production-optimised delivery.
Primary + replica pattern. Writes to both, reads prefer primary with auto-fallback. Zero-downtime migrations.
The AI module connects SiteEngine to the full pipeline - Baibelfish ingestion, DeepThought staging, query classification, prompt assembly, conversation context, and the Efficiency Engine - through a single admin interface.
Create, configure and monitor AI experts from the dashboard. Set voice profiles and emotional masking.
Upload documents and trigger Baibelfish ingestion directly from the platform. Monitor progress in real time.
Per-expert and per-query token usage. Citation quality monitoring and confidence distributions.
25+ years of running regulated information systems. The compliance dashboard treats EU AI Act and US AI framework obligations as first-class concerns, governed through the same control plane as the platform itself. Deploy on-premises, in your VPC, or air-gapped. RBAC and connector-based isolation enforce data governance at the query layer.
On-premises / VPC / air-gapped
Full deployment flexibility with Ollama or local LLMs for zero external calls.
GDPR via connectors & RBAC
Purpose limitation via row-level security. Cascading soft-delete. Full audit logging.
EU AI Act & US AI framework
Technical documentation, risk management logs, provenance trails, NIST AI RMF alignment - captured in the compliance dashboard, not a separate spreadsheet.
Human-in-loop refinement
Flag, review and resolve ambiguous entities, citations and extractions directly from the governance framework.
Information management, document ingestion, AI pipeline, Efficiency Engine and compliance monitoring - administered together, with 27 years of production reliability underneath. Still running on the same architecture principles 27 years on.