Entity Coherence Engine – AI Search Intelligence Platform_

Project Overview

Search is no longer keyword-first. AI search engines interpret content through entities, relationships, semantic depth, and topical authority.

Traditional SEO tools measure rankings and keywords. They do not measure entity dominance, semantic authority, or structural coherence — the signals AI systems use to synthesize answers.

The Entity Coherence Engine was built to solve that gap.

It analyzes your content and competitor pages locally, extracts semantic clusters, calculates dominance scores, and produces a structured AI-readiness audit — without relying on external LLM APIs.

This is not an SEO tool. It is an AI search visibility intelligence engine.

What It Does

The system ingests:

• Your URL
• Competitor URLs
• Extracted entities and topical clusters

Then computes:

• Semantic Authority Index
• Competitive Dominance Score
• Cluster-Level Gap Analysis
• Missing Topic Detection
• Historical Trend Tracking
• AI-Ready PDF Intelligence Reports

Every score is calculated from a deterministic backend engine — the UI does not manipulate or reinterpret scoring.

Core Capabilities

• Entity Cluster Extraction

  Identifies dominant semantic clusters across your page and competitor pages.

• Competitive Dominance Engine

  Quantifies whether you are dominant, competitive, or outmatched per topic cluster.

• Cluster Importance Scoring

  Measures semantic weight based on coverage density and competitive distribution.

• Strategic Intelligence Layer

  Generates cluster-specific insights and recommendations based on measurable gaps — not generic AI summaries.

• Historical Authority Tracking

  Tracks semantic authority over time to visualize structural growth.

• Local-First Architecture

  Runs via Python NLP engine and TypeScript backend without third-party AI dependencies.

The Challenge

AI search systems do not rank pages the same way traditional SERPs do.

They:

• Synthesize answers
• Merge entity relationships
• Prioritize topical depth
• Evaluate semantic coherence

Most tools still optimize for keyword density.

There was no lightweight, self-hosted tool to measure AI-native visibility metrics.

The Solution

Built a full-stack semantic intelligence engine composed of:

Backend:

• Python-based NLP cluster engine
• Deterministic scoring system
• PostgreSQL storage
• Trend tracking service
• PDF export generation

Frontend:

• React + TypeScript dashboard
• Black/orange layered dark UI
• Interactive cluster breakdown
• Expandable intelligence panels
• Fully responsive trend visualization

The system operates with strict backend authority — the frontend renders scores without modifying logic.

Why It Matters

AI search visibility is becoming the next ranking layer.

Brands will need:

• Entity dominance
• Topic completeness
• Structural coherence
• Competitive semantic superiority

This engine provides a measurable framework for that transition. It is designed as a proof-of-concept foundation for a larger AI search intelligence platform.

Future Expansion

• Real-time crawling engine
• Multi-page domain authority aggregation
• Entity graph visualization
• AI answer simulation scoring
• SERP-to-AI drift tracking
• Team collaboration layer
• API access for SaaS integration