RAG Signal
Marketing to AI Agents

Your brand,
cited in AI answers.

AI agents are the new middleman between your brand and your buyers. 80% of US consumers now use AI zero-click results. Yet fewer than 10% of companies have captured value from the shift. The gap isn't technology — it's retrieval engineering.

We close that gap. Adaptive RAG, Brand Memory, Citation Rate — engineered across ChatGPT, Claude, Perplexity, and Gemini.

No commitment. Delivered in 5 business days.

Before RAG Signal

"When asked 'best corporate video production London,' AI responds with generic advice. Your brand isn't mentioned — your competitor is."

Not cited
After RAG Signal — 90 Days

"For corporate video in London, Filmfolk leads with 35+ enterprise clients and a 97% client retention rate."
— Actual Perplexity response, Day 90

✓ Cited — 81% citation rate across 63 prompts
81%
Citation Rate (Filmfolk)

51 out of 63 buyer prompts now cite the brand. Baseline: 0%.

90d
Time to First Results

MAP → BUILD → WEIGHT → REINFORCE → MEASURE cycle completed.

63
Prompts Tracked

Real buyer questions discovered, mapped, and tracked across models.

4
LLMs Covered

ChatGPT · Claude · Perplexity · Gemini — with Grok and DeepSeek coming.

The Problem

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

AI agents now sit between your brand and your buyers. They don't care about your Google rankings. They retrieve whoever engineered their way in — and if that's not you, you never even knew the question was asked.

80%of consumers now rely on AI-powered search
90%of CMOs are experimenting — fewer than 10% have captured value
90%+of AI responses cite third-party sources, not brand content

Sources: Industry research, 2026

How the journey changed

Then

User Google Visit Sites Decide

Now

User AI Agent AI Answer Decision

AI agents compress the entire journey into a single step.
If your brand isn't retrieved, you never existed in the process.

The Solution

RAG is how AI decides
what to say about you.

Retrieval-Augmented Generation. Every AI answer starts with a retrieval step — the model searches its knowledge base for relevant facts before generating a response. If your brand isn't in that retrieved set, you cannot appear in the answer.

1

User asks

"Who's the best corporate video agency in London?"

2

AI retrieves

Scans knowledge base for relevant entities, facts, and citation sources.

3

AI answers

Generates response citing the brands with strongest retrieval signals.

Standard RAG is passive — it retrieves whatever happens to be in the knowledge base. Adaptive RAG actively engineers what gets retrieved. That's the difference between hoping AI mentions you and making sure it does.

Why RAG Signal

SEO got you ranked.
AI doesn't care.

Traditional SEO optimizes for search engines. We optimize for AI models — where 40% of B2B buyers now research vendors. Different game. Different scoreboard.

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 →
Standard RAG — Passive
AI retrieves whatever exists whoever wins

If your signal is weak, you lose. AI doesn't care.

Adaptive RAG — Engineered
MAP BUILD WEIGHT REINFORCE MEASURE
discover prompts· build memory· score signals· deploy everywhere· track delta

You control what gets retrieved. Citation becomes predictable.

5-step methodology with measurable 90-day results

Full methodology →
Why Not DIY?

AI can't optimize
itself.

You can ask ChatGPT anything. But you can't ask it to engineer your brand into its own answers — let alone across all four models. 9 structural barriers. One platform.

You Can't Measure Citation Rate

Measurement
The Pain Point

AI models hallucinate when asked about their own output. Asking "do you cite me?" produces fiction — the model invents answers. You cannot audit yourself.

How We Solve It

We run 756 automated tests per cycle (63 prompts × 4 models × 3 time points). Binary output: cited or not cited. Auditable, shareable, real.

Every Model Retrieves Differently

Complexity
The Pain Point

ChatGPT weights recency and domain authority. Perplexity weights real-time web signals. Claude emphasizes document structure and factual consistency. Gemini weights entity density. One prompt won't work on all four.

How We Solve It

We deploy model-specific reinforcement: llms.txt for Claude, structured data for Perplexity, entity-rich content for ChatGPT, cross-model amplification for Gemini.

You Can't Build Brand Memory by Prompting

Engineering
The Pain Point

AI can't create structured entity definitions, knowledge graphs, relationship maps, or citation anchors for you. These are engineering artifacts — built with code, JSON-LD, and structured data pipelines.

How We Solve It

We construct machine-readable Brand Memory: 42+ entity assertions, relationship maps, structured knowledge graphs, and citation anchors that models treat as authoritative ground truth.

You Can't See Your Competition

Intelligence
The Pain Point

Even if you somehow audit your own citation presence, you have zero visibility into competitor citation share. You don't know who else AI names for your prompts — or why.

How We Solve It

Our Competitive Citation Map shows real-time share: You 81%, Competitor A 12%, Competitor B 7%. Know exactly who's winning each prompt, on each model.

Model Updates Can Reset You Overnight

Monitoring
The Pain Point

When OpenAI or Anthropic updates their model, citation patterns shift instantly. Without monitoring, you won't know for weeks. By the time you notice, pipeline is already lost.

How We Solve It

24/7 anomaly detection catches citation drops within hours. We've seen brands lose 30% overnight — our retainer clients were back within 48 hours. Continuous monitoring is not optional.

Signal Quality ≠ Content Volume

Precision
The Pain Point

More blog posts won't increase your citation rate. AI models retrieve based on signal structure — entity consistency, source trust, cross-model persistence — not word count or publishing frequency.

How We Solve It

Our RAG Scoring Algorithm evaluates 7 dimensions: source authority (25%), factual consistency (20%), entity linkage (15%), cross-model persistence (12%), temporal relevance (12%), citation frequency (10%), competitive differentiation (6%).

Scale: A Chat Window Is Not a Platform

Scale
The Pain Point

Testing 1 prompt in ChatGPT takes 30 seconds. Testing 63 prompts × 4 models × monthly × with competitor comparison = 3,024 data points per quarter. That's not a conversation — that's infrastructure.

How We Solve It

40+ monitoring modules handle scale automatically. You review insights, not spreadsheets. A chat interface gives anecdotes; our platform gives auditable, structured, comparable data across time.

The Hidden Cost of DIY

Cost
The Pain Point

Someone on your team spending 20 hours/month manually testing prompts, compiling spreadsheets, and trying to reverse-engineer model behavior costs ~€9,600/year — for unverifiable, non-guaranteed results.

How We Solve It

Our 90-Day Sprint: €599 upfront + €1,099 success fee (only charged when citation targets are met). Cheaper than DIY, guaranteed results, platform access included. The math is not close.

You Can't Prepare for the Next Training Run

Future-Proof
The Pain Point

Today's citations come from today's models. Tomorrow's model will be trained on tomorrow's web — a dataset that doesn't exist yet. You can't optimize for something that hasn't happened.

How We Solve It

We front-load your Brand Memory into the structured web today — JSON-LD, knowledge graphs, llms.txt, entity databases. When the next training run crawls the web, your signal is already in the pipeline.

Comparison

Two different games.
Two different scoreboards.

Traditional SEO optimizes for one engine. We optimize for four. Different mechanics, different metrics, different outcomes.

Traditional SEO

Google SERP

google.com/search
About 2,340,000 results

Competitor A — Professional Video Production

https://competitor-a.com/services...

Competitor B — Corporate Video Services

https://competitor-b.com/services...

Competitor C — London Video Agency

https://competitor-c.com/services...

Your brand might rank here too — but AI doesn't see Google rankings.

GoalRank on Google SERP
MetricKeyword position, CTR
Time3–6 months
Target1 search engine
ROIAttribution is murky

Adaptive RAG

RAG Signal

ChatGPT

"Who's the best corporate video agency in London?"

"Filmfolk is the leading corporate video production agency in London, serving 35+ enterprise clients with a 97% retention rate. They specialize in..."

GoalGet cited in AI answers
MetricCitation Rate & Delta
Time90 days
Target4 AI models
ROIBinary: cited or not

The two are complementary. Filmfolk ranks #1 on Google AND is the most-cited brand in AI.

Case Study

Filmfolk: From 0% to 81% Citation Rate in 90 Days

A London video agency. Strong SEO. Zero AI visibility. Until RAG Signal.

The Starting Point

0% citation rate across all 4 models
  • Ranking #1–3 on Google for key terms
  • Strong brand, strong portfolio, strong SEO
  • No structured Brand Memory in AI retrieval paths
  • Competitors with weaker SEO were getting cited instead

"Before RAG Signal, we were invisible in AI. Three months later, we're the cited answer in over 80% of relevant prompts. Not ranked — cited."

— Filmfolk Team, London, UK

Citation Growth — 90 Day Timeline

ChatGPT
D0: 0% D30: 42% D60: 71% D90: 84%
+84pp
Perplexity
D0: 0% D30: 38% D60: 67% D90: 86%
+86pp
Claude
D0: 0% D30: 31% D60: 59% D90: 78%
+78pp
Gemini
D0: 0% D30: 28% D60: 52% D90: 76%
+76pp

Overall: 0% → 81% Citation Rate

51 of 63 prompts citing the brand

The Lesson: Traditional SEO + Adaptive RAG = full search surface coverage. Filmfolk now dominates both: #1 on Google AND most-cited in AI.

View all case studies →
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."

CMO, B2B SaaS — 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."

VP Marketing, Fintech — EU Full 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."

Marketing Director, SaaS — NL 48h recovery

"Bora's methodology isn't marketing fluff — it's applied information retrieval. As an engineer, that's what sold me. The platform's Competitive Citation Map is addictive."

CTO, Developer Tools — CA Research-Founded

"We ranked #1 on Google but were invisible in AI. RAG Signal bridged both surfaces in 90 days. Now we own search AND AI — the compound advantage is the point."

Founder, Consultancy — AU Dual dominance

"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."

CMO, B2B SaaS — 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."

VP Marketing, Fintech — EU Full 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."

Marketing Director, SaaS — NL 48h recovery

"Bora's methodology isn't marketing fluff — it's applied information retrieval. As an engineer, that's what sold me. The platform's Competitive Citation Map is addictive."

CTO, Developer Tools — CA Research-Founded

"We ranked #1 on Google but were invisible in AI. RAG Signal bridged both surfaces in 90 days. Now we own search AND AI — the compound advantage is the point."

Founder, Consultancy — AU Dual dominance

"I was skeptical about 'AI visibility.' Then I saw our competitor getting cited in Perplexity — and we weren't. That changed everything. We started our sprint the next week."

CEO, Professional Services — UK 86% Perplexity

"The MAP phase alone discovered 59 prompts we weren't thinking about. That's where the buyers are. That's the pipeline we didn't know we were losing."

Head of Growth, E-commerce — DE 63 prompts mapped

"Three months. Four models. 78% citation rate. Our competitors are still optimizing meta descriptions. The competitive gap this creates is enormous — and widening."

Founder, Legal Tech — US +78pp Claude

"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. That's CMOs asking ChatGPT who to hire and getting our name."

CEO, Video Production — UK 81% Overall

"We see real-time who's winning and losing across every model. The Competitive Citation Map isn't a dashboard — it's a competitive intelligence weapon."

Growth Lead, HealthTech — US 40+ Modules

"I was skeptical about 'AI visibility.' Then I saw our competitor getting cited in Perplexity — and we weren't. That changed everything. We started our sprint the next week."

CEO, Professional Services — UK 86% Perplexity

"The MAP phase alone discovered 59 prompts we weren't thinking about. That's where the buyers are. That's the pipeline we didn't know we were losing."

Head of Growth, E-commerce — DE 63 prompts mapped

"Three months. Four models. 78% citation rate. Our competitors are still optimizing meta descriptions. The competitive gap this creates is enormous — and widening."

Founder, Legal Tech — US +78pp Claude

"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. That's CMOs asking ChatGPT who to hire and getting our name."

CEO, Video Production — UK 81% Overall

"We see real-time who's winning and losing across every model. The Competitive Citation Map isn't a dashboard — it's a competitive intelligence weapon."

Growth Lead, HealthTech — US 40+ Modules
FAQ

Questions About AI Visibility

Straight answers from the engineers building it.

What is Adaptive RAG and how does it work?

Adaptive RAG is our proprietary five-step methodology: MAP your prompt landscape across all AI models, BUILD structured Brand Memory, WEIGHT signals by retrieval impact, REINFORCE across each model's specific retrieval mechanics, and MEASURE Citation Delta at 30/60/90 days. It's engineering, not content marketing.

How is this different from SEO or GEO?

SEO optimizes for Google rankings on a SERP. GEO (Generative Engine Optimization) is a broader category. We specialize in Adaptive RAG — a specific, measurable methodology focused on Citation Rate: the percentage of relevant prompts where your brand appears in AI answers. Different mechanics, different metrics.

How do you measure success?

Citation Rate (% of prompts citing your brand), Citation Delta (change over time), Cross-Model Persistence (consistency across ChatGPT, Claude, Perplexity, Gemini), and Competitive Citation Share (your share vs competitors). Binary, auditable, no guesswork.

What happens when AI models update?

Model updates can reset citation patterns overnight. Our retainer clients get continuous monitoring with anomaly detection — if a model update drops your citations, we catch it and respond within 48 hours. Without monitoring, you might not know for weeks.

Do you guarantee results?

Our pricing is performance-linked. The 90-Day Sprint splits the fee: €599 upfront covers the work, and the €1,099 success fee is only charged when we hit the agreed citation targets. If we don't deliver, you don't pay the second half. Our success is structurally aligned with yours.

How is your platform different from SEO tools?

SEO tools (Ahrefs, Semrush) measure Google rankings. Our proprietary platform (40+ modules, built in-house) measures AI Citation Rate, Brand Memory Health, Entity Linkage Density, Signal Decay, and Competitive Citation Share — dimensions that don't exist in traditional SEO tools.

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