Gregius Intelligence
The continuous improvement layer for AI workflows in WordPress
Every user interaction generates signals. Gregius Intelligence caches, scores, and applies those signals to continuously refine relevance, governance, and retention across your entire WordPress site — keeping your AI responses faithful, grounded, and improving with every engagement.
Tuning Control Plane
An executive dashboard that exposes verified setting surfaces, clear guardrails including defaults, bounds, and validation rules, and per-connection overrides with reset and rollback behavior. Editors and operators gain direct command over AI parameters without touching code, turning configuration management from a developer dependency into an operational workflow.
Agentic RAG Intelligence
A continuous improvement engine that records, scores, and applies feedback signals across every visitor session. Journey continuity preserves user context across page navigation, interaction history persists and retrieves prior sessions with audit integrity, and progressive summaries compress long-running dialogues to maintain stateful experiences on stateless language models.
Continuous Improvement
Each user interaction generates signals that are cached, scored for faithfulness and groundedness, and applied to incrementally refine relevance for contracts, policy, governance, and retention — transforming your AI from a static responder into a self-improving system.
Web Enhanced Assistant
Every visitor session should feel continuous, not fragmented across page loads.
Site-wide journey continuity and interaction history give users persistent access to previous sessions, ensuring conversations retain context as visitors navigate your content. This reduces cognitive friction and increases engagement depth on every return visit.
Next Best Action
Context-aware recommendations transform passive reading into guided discovery.
A cache layer driven by faithfulness and groundedness scoring maps user context to generate frictionless, reusable recommendations and discovery paths. This keeps visitors engaged without relying on generic, one-size-fits-all content suggestions.
Editorial Curation
Editorial judgment must remain the ultimate arbiter of content priority.
Enables editorial teams to control system scoring by enforcing specific content boosts, quotas, and quality gates. Editors determine which content takes precedence during retrieval events, preserving human oversight over automated AI ranking behavior.
Relevance Feedback
AI accuracy should compound with usage, not plateau after deployment.
Records interaction signals and applies automated boost and demote policies integrated with freshness aggregation. This closed feedback loop means response quality improves incrementally over time, without requiring manual retraining cycles or external tuning platforms.
Tuning Control Plane
Confident AI operations require verifiable, reversible configuration management.
Exposes a verified setting surface with clear guardrails — defaults, bounds, and validation — while supporting per-connection overrides with quick reset and rollback. This gives operators the confidence to experiment with AI parameters knowing every change is traceable and reversible.
Features
Designed to carry session context seamlessly across page loads and return visits. Every session stays coherent. Every claim carries a verifiable source. The result is an AI experience that feels continuous, confident, and transparent.
Interaction History
Persist, retrieve, and safely reuse prior interaction sessions while preserving contract boundaries and audit integrity across the entire user journey.
Journey Continuity
Preserve user conversation continuity across page navigation with persistent interaction history and recursive progressive summaries.
Progressive Summary
Recursive context compression that maintains a stateful user experience on stateless language model inference for extended chat sessions.
Faithfulness
Computes, exposes, and persists claim-evidence scoring signals, giving operators measurable confidence in every AI response delivered to users.
Groundedness
Enforces manifest-constrained retrieval and source-attribution-ready provenance for transparent, auditable AI behavior across every interaction.
Questions, answered
Want to know more? Check out these answers to common questions.
Gregius Intelligence is a continuous improvement layer for AI workflows in WordPress. Built as an extension for Gregius Data, it introduces advanced user-experience controls, session continuity tools, and a feedback-driven optimization engine to elevate your self-hosted AI infrastructure.
This extension is designed for high-traffic content sites, wikis, and enterprise WordPress platforms that require persistent chat experiences. It serves teams that need to retain user context across page loads and dynamically optimize AI response relevance based on editorial curation and user feedback.
Yes. Gregius Intelligence is an add-on built using the core plugin’s native actions and filters. It requires a functioning Gregius Data installation, leveraging its foundational self-hosted control plane, registered language models, and PostgreSQL semantic and vector execution layer.
The platform uses recursive context compression and progressive summaries to maintain long chat sessions on stateless language models. It persists, retrieves, and reuses prior interaction sessions securely, ensuring a continuous user experience as visitors navigate across different pages on your site.
The Tuning Control Plane is an executive dashboard capability that exposes verified setting surfaces to manage your AI. It includes clear guardrails like defaults, boundaries, and validation rules, while supporting per-connection overrides with quick reset and rollback behaviors.
Yes. The Editorial Curation features give editors direct command over system scoring. Teams can enforce specific content boosts, quotas, and quality gates to control which data takes priority during retrieval events.
The system collects interaction signals and relevance feedback to apply automated boost and demote policies. It caches this feedback while computing and exposing explicit claim-evidence scoring signals to prioritize response faithfulness and groundedness.
The Web Enhanced Assistant provides site-wide journey continuity and interaction history. Next Best Action maps user context to generate frictionless, reusable recommendations and discovery paths, keeping users engaged via a cache layer driven by source provenance.
Gregius Intelligence will be available as a yearly subscription. The license will provide ongoing updates, feature enhancements, and compatibility support.
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