Platform

Your AI visibility
command center.

Every RAG Signal engagement includes access to our proprietary platform — built to track, measure, and improve your brand's presence across all major AI models in real time.

Get access → View services

Under the Hood

Automated. Measurable. Adaptive.

The platform runs continuous prompt testing, citation tracking, and Brand Memory maintenance across all major AI models — automatically.

ragsignal — pipeline runner

$ python main.py --module all --domain filmfolk.co.uk

Loading client config... OK

✓ visibility — LLM SERP tracking (Perplexity Sonar)

✓ prompt-audit — 63 prompts tested across ChatGPT, Claude, Perplexity, Gemini

✓ brand-memory — Knowledge base freshness check + update

✓ competitors — Competitive citation analysis (8 competitors tracked)

✓ citations — Domain citation tracking across AI models

✓ entity-signals — Brand-role-category consistency scoring

✓ schema — Schema + meta generation (Claude Haiku)

✓ llmstxt — AI discovery file generation + deploy

✓ heal — Issue detection and auto-resolution

→ Citation rate: 81% (↑ from 0%). Report saved.

Core Modules

Everything in one system.

The platform covers every layer of AI visibility — from initial audit to ongoing maintenance and competitive monitoring.

AI Visibility

LLM SERP TrackingTracks your brand mentions across ChatGPT, Claude, Perplexity, and Gemini in real time using Perplexity Sonar.

Brand Memory

Knowledge Base BuilderBuilds and maintains your curated brand knowledge base — the structured entity layer AI systems retrieve from.

Prompt Audit

Prompt Reality TestingRuns real buyer prompts across all major AI models and captures citation data before and after every sprint.

Competitors

Competitive Citation AnalysisTracks which competitors are being cited instead of you — and monitors their signal changes over time.

Entity Signals

Entity IntelligenceMaps brand-role-category relationships and scores entity confidence across AI models. Identifies gaps before they cost citations.

Schema & Meta

Structured Data GenerationAI-powered schema and meta generation via Claude Haiku — optimized for retrieval, not just crawling.

AI Discovery

llms.txt DeploymentGenerates and deploys your llms.txt file — the emerging standard for telling AI systems what your brand is and does.

Auto-Heal

Issue Detection & ResolutionDetects broken signals, missing metadata, and configuration errors — and resolves them automatically.

Dashboard

See exactly where you stand.

The RAG Signal dashboard gives you a real-time view of your AI visibility — citation rates, prompt coverage, competitor deltas, and Brand Memory health — all in one place.

→Citation rate over time (per model)
→Prompt coverage heatmap
→Competitor citation delta
→Brand Memory freshness score
→Entity confidence per AI model
→Action items and sprint progress

Get platform access →

Live Citation Score

81%

Overall

51/63

Prompts

+81pp

Delta

Tech Stack

Claude Haiku

Perplexity Sonar

Database

Supabase

Frontend

React + Vite

Proprietary

Brand Memory™ — only at RAG Signal.

Brand Memory is our proprietary knowledge layer — a structured, curated representation of your brand that AI retrieval systems can read, trust, and cite. It maps your entity relationships, source trust hierarchy, and factual proof points into a format optimized for how LLMs retrieve and rank information. No other agency builds or maintains this layer.

Entity Mapping

AI models understand who you are, what category you own, and why you're the right answer.

Source Trust Hierarchy

Owned, earned, structured, and third-party signals weighted for maximum retrieval priority.

Freshness Management

Brand Memory decays as models update. We maintain it continuously so your citations don't drift.

Get Access

Platform access is included in every engagement.

Start with a free AI presence audit. If we're a good fit, you get full platform access as part of the sprint or retainer.