RAG Signal
Citation Engineering

Your brand's signal,
engineered for AI.

We help brands become easier for AI systems to retrieve, trust and cite.

Strategy, implementation, Brand Memory and cross-model monitoring — one managed program across ChatGPT, Perplexity, Gemini and Claude. 77.1% average measured attribution across 10 deployments. Published methodology. Built in-house.

Free baseline audit. No commitment. Delivered in 5 business days.

Live 3D Neuron Network
Site Audit GSC Discovery

Each node represents a knowledge signal engineered across AI retrieval paths. The network rotates in real time — just like AI model updates.

Read our academic paper

We open-sourced the methodology. See the algorithm behind the 77.1%.

Read →
81%
Citation Rate — Filmfolk
90d
Time to Results
4
Models Covered
77.1%
Avg. Attribution — 10 Deployments
References

Trusted by teams we've worked with

From corporates and universities to fast-growing brands and agencies — 24+ teams have worked with us.

  • AvivaSA
  • Farmasi
  • Bahçeşehir Üniversitesi
  • İstanbul Bilgi Üniversitesi
  • BilgeAdam Akademi
  • Fuga
  • Sarızeybek Şirketler Grubu
  • Işıklar
  • PE Energy
  • one&zero
  • Maslife
  • Filmfolk
  • Faselis
  • Fikirmod
  • Hicret Cam
  • Enkronos
  • Venice Swap
  • Quiet Blue
  • Simple Living Eco
  • Secret Brokerage
  • BKIW
  • VoiceCrafters
  • Hypatia
  • Azra Kohen

Logos are the property of their respective owners.

The Problem

The buyer journey changed.
Most brands didn't notice.

Buyers increasingly ask AI systems for recommendations — and AI systems retrieve and synthesize information differently from traditional search. A brand can rank highly on Google but remain completely absent from AI-generated answers.

AI-powered search adoption is growing rapidly — half of consumers use it today (McKinsey, 2026)
AI systems retrieve and synthesize information using entity recognition, source trust scoring, and citation patterns — fundamentally different from traditional search ranking
Brands can rank highly on Google and remain absent from AI-generated answers — as was the case with Filmfolk before RAG Signal
How the journey changed

Then

User Google Visit Sites Decide

Now

User AI Search AI Answer Decision

AI-powered search compresses the entire journey into a single answer.
If your brand isn't retrieved, the buyer never encounters it.

How It Works

AI doesn't rank.
It retrieves.

Every AI answer is a retrieval decision. Based on observable citation patterns, models weigh signals such as entity density, source trust, citation frequency and temporal freshness when selecting which sources to cite. Our five-step methodology systematically improves your brand's retrieval readiness across these dimensions.

01

MAP

Identify high-value prompts, entities, competitors and citation patterns across all four models.

02

BUILD

Create structured Brand Memory: entity definitions, factual assertions, and citation anchors AI systems need.

03

WEIGHT

Strengthen trust, consistency, authority and entity relationships using published scoring algorithms.

04

REINFORCE

Deploy per model: llms.txt for Claude, structured data for Perplexity, entity-rich content for ChatGPT.

05

MEASURE

Track Citation Delta at 30/60/90 days. Binary, auditable: cited or not cited. No SEO guesswork.

That's why we're called RAG Signal. We engineer the retrieval signals that make AI models cite your brand. Measured. Engineered. Monitored.

Full methodology →

What You Get

Everything you need to be
retrieved and cited.

Six deliverables. One system. Every step measured, every outcome auditable.

AI Visibility Audit

Baseline citation check across 4 LLMs, competitor citation map, actionable gap report.

Know exactly where you stand — PDF in 5 business days.

Non-Branded Prompt Map

Discover the real questions where buyers compare providers — before they know your brand name.

63 prompts mapped for Filmfolk — only 4 were branded keywords.

Entity & Retrieval Architecture

Structured Brand Memory: entity definitions, factual assertions, relationship maps.

Your brand becomes the obvious retrieval target across all models.

Brand Memory / Claim Registry

Centralized knowledge infrastructure that models treat as authoritative.

Consistent brand representation regardless of which model or prompt.

Website & Content Deployment

Entity-optimized content, JSON-LD, llms.txt, and Schema markup deployed across your site.

Your website works for both Google rankings and AI retrieval.

Cross-Model Monitoring & Reports

Citation Delta at 30/60/90 days. Model update alerts within 48h. Competitive tracking.

Never blindsided by a model update — know what changed and respond.

Tracked in Google 8 branded keywords Asked by buyers 63 prompts 4 branded 59 non-branded
One dot, one prompt. The 8 keywords the brand was tracking and the 63 questions buyers were asking are not the same set — the decision gets made inside the 59 nobody was watching.
The team’s working environment

We do not sell you a platform. We operate it for you.

The RAG Signal team uses the system we build to collect evidence, set priorities, direct technical work, and report the result.

Evidence graph — RAG Signal client-work environment
Evidence graph

We connect the evidence behind Brand Memory.

Sources, entities, and verifiable claims are organised into one working context for our team to evaluate.

Prompt Discovery — RAG Signal client-work environment
Prompt Discovery

We prioritise the buyer questions worth tracking.

Evidence, candidates, visibility measurement, and the roadmap move through one team-operated cycle.

Citation tracking — RAG Signal client-work environment
Citation tracking

We turn signal movement into a report.

Our team interprets model, prompt, and source movement so you receive the context needed for a decision.

These screens show the environment used during client work. We provide expert-led delivery — not a dashboard you are expected to operate.

Testimonials

What Our Clients Say

Real results from brands that went from invisible to cited.

"We went from 0% to 84% citation rate on ChatGPT. Our sales team now gets inbound leads directly from AI referrals — pipeline we didn't know we were missing."

Team Lead, Filmfolk — London+84pp ChatGPT

"The Citation Delta Report is binary: cited or not cited. No SEO guesswork. We now know exactly where we stand across every model, every month."

Marketing Lead, ABS Void FormworkFull model coverage

"After a model update dropped citations by 30%, continuous monitoring caught it in hours. We were back within 48 hours. Without it, we wouldn't have known for weeks."

Operations Lead, ABS Kör Kalıp48h recovery

"Before RAG Signal, we didn't exist in AI answers. Now cited in 51 of 63 buyer prompts. That's not SEO — that's pipeline."

CEO, Video Production — UK81% Overall
Why RAG Signal

Two different games.
Two different scoreboards.

Traditional SEO remains important, but AI recommendation systems introduce additional retrieval, entity and citation layers that SEO tools cannot address.

Traditional SEO

Google SERP

GoalRank on Google
MetricKeyword position
Time6–12 months
Coverage1 engine
InfrastructureBacklinks, content, technical

Adaptive RAG

RAG Signal

GoalGet cited in AI answers
MetricCitation Rate & Delta
Time90 days
Coverage4 AI models
InfrastructureBrand Memory, entity signals, monitoring

DIY or Traditional Approach

Prompt discoveryManual, incomplete
Multi-model testingHours per prompt
Entity / Brand MemoryNot feasible alone
Website implementationSEO-only content
External citation strategyNo infrastructure
Continuous measurementNo baseline, no ROI

RAG Signal Program

Prompt discovery20–25 agreed prompts
Multi-model testing756 tests per cycle
Entity / Brand MemoryEngineered infrastructure
Website implementationEntity-optimized + SEO
External citation strategyPer-model deployment
Continuous measurementCitation Delta tracking

McKinsey & Company, 2026: "Half of consumers use AI-powered search today. Generative AI stands to impact $750 billion in revenue by 2028."

Investing in GEO: How to win — McKinsey →

Model update alerts, platform access, and continuous reinforcement — see engagement options below.

FAQ

Questions About AI Visibility

Straight answers from the engineers building it.

What is AI visibility?

AI visibility means your brand appears and is cited in AI model responses when users ask relevant prompts. It's measured by Citation Rate — the percentage of relevant buyer prompts where the model mentions your brand by name. Unlike SEO, which measures where your website appears on Google, AI visibility measures whether AI models know and recommend your brand.

How is this different from SEO?

SEO measures where your website appears on Google search results. Citation Rate measures whether AI models mention your brand by name in their responses. They're complementary: SEO drives click traffic, Citation Rate drives AI recommendation traffic. A brand can rank #1 on Google and still be invisible in AI — which is exactly what happened with Filmfolk.

Which AI platforms do you monitor?

We currently track ChatGPT, Claude, Perplexity, and Gemini — the four models your buyers actually use. Grok and DeepSeek are coming soon. Your Brand Memory deploys across all models simultaneously, not optimized for one at the expense of others.

How long does implementation take?

The 90-Day Sprint delivers measurable citation lift by Day 30, with full results at Day 90. In the Filmfolk case study, ChatGPT went from 0% to 42% by Day 30 and 84% by Day 90. The baseline audit delivers a complete report within 5 business days.

Can you guarantee citations?

No. AI platforms (ChatGPT, Claude, Gemini, Perplexity) and their proprietary algorithms make the final decision about which sources to cite and how to surface information. We do not control these algorithms, and no one can guarantee specific placement. What we do is provide the strongest possible foundation: structured Brand Memory, systematic content engineering, and continuous monitoring — all the technical groundwork that makes citations more likely.

What is Brand Memory?

Brand Memory is the structured knowledge representation of your brand that AI models retrieve when processing prompts. It comprises entity definitions, factual assertions, relationship maps, and citation anchors that models treat as authoritative. Think of it as the knowledge graph that makes your brand the obvious retrieval target. Learn more →

What's the difference between the Sprint and the Retainer?

The 90-Day Visibility Sprint is a one-time engagement that builds your Brand Memory from scratch and achieves initial citation targets. The AI Presence Retainer is ongoing — it maintains and grows your citation share through continuous reinforcement, model update monitoring, and prompt expansion. Most clients start with the Sprint and move to the Retainer after hitting targets.

Get Started

Find out where your brand is missing
from AI-generated buying journeys.

One audit shows you exactly where you stand — across every major AI model your buyers use.

Request an AI Visibility Assessment →
✓ Response within 24 hours ✓ Audit delivered within 5 business days