Your brand,
cited in AI answers.
The shift from the attention economy to the trust economy is already underway. 90% of CMOs are experimenting with AI. Fewer than 10% have captured value. 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.
"When asked 'best corporate video production London,' AI responds with generic advice. Your brand isn't mentioned — your competitor is."
Not cited"For corporate video in London, Filmfolk leads with 35+ enterprise clients and a 97% client retention rate."
— Actual Perplexity response, Day 90
51 out of 63 buyer prompts now cite the brand. Baseline: 0%.
MAP → BUILD → WEIGHT → REINFORCE → MEASURE cycle completed.
Real buyer questions discovered, mapped, and tracked across models.
ChatGPT · Claude · Perplexity · Gemini — with Grok and DeepSeek coming.
Built for the AI ecosystem
See What We Measure
Every engagement includes access to our proprietary platform built in-house — 40+ modules tracking every dimension of AI visibility, developed and maintained by our engineering team.
Built in-house.
40+ modules deep.
Our platform isn't a wrapper around someone else's API. Every module — from entity intelligence to citation scoring — was built by our engineering team over two years of applied research.
Brand Memory Engine
Structured knowledge graphs that AI models retrieve and cite. Entity definitions, factual assertions, relationship maps, citation anchors — all built as machine-readable data, not blog posts.
42 entity assertions activeKnowledge Base
Curated, versioned repository of your brand's structured knowledge. Exportable as JSON-LD. Portable to any system. Updated continuously as your brand evolves, products launch, and markets shift.
Full JSON-LD exportCitation Intelligence
Real-time tracking of your citation rate across every prompt and model. Per-model breakdowns, framing analysis (positive/neutral/negative), and Citation Delta tracking at 30/60/90 days.
756 tests per cyclePrompt Discovery
Mine Google Search Console, competitor citation patterns, LLM query logs, and category-specific buyer journeys to build a comprehensive prompt map. Filmfolk: 8 keywords → 63 prompts.
63 prompts discoveredPrompt Tracking
Continuous monitoring of all discovered prompts across ChatGPT, Claude, Perplexity, and Gemini. Model-by-model, prompt-by-prompt citation presence tracking with historical trendlines.
4 models × 63 promptsContent Gap Analyzer
Identify exactly which prompts cite competitors but not you. Prioritized gap report with signal-level recommendations — not "write more content," but "build this entity assertion, strengthen this citation anchor."
Competitor gap scoringAI Content Production
Generate entity-optimized content designed for AI retrieval — not SEO keyword density. Structured for RAG systems, built for vector proximity, deployed across llms.txt, knowledge graphs, and semantic web surfaces.
Entity-structured outputRAG Scoring Algorithm
Proprietary 7-dimension signal evaluation: source authority (25%), factual consistency (20%), entity linkage (15%), cross-model persistence (12%), temporal relevance (12%), citation frequency (10%), competitive differentiation (6%).
7 scoring dimensionsCompetitive Citation Map
Real-time competitive intelligence across all models. See who's being cited for every prompt, on every model. Track competitor movements, identify threats, and measure your Citation Share over time.
You 81% / Comp A 12% / Comp B 7%How Adaptive RAG Works
A structured, repeatable five-step methodology — not guessing, not content spraying.
Prompt Landscape
Discover every real buyer question where your brand should appear. We found 63 prompts for Filmfolk — only 4 were branded.
8 keywords → 63 prompts
Brand Memory
Construct structured knowledge that AI models retrieve. Entity definitions, factual assertions, citation anchors.
42 entity assertions
Score Signals
Our algorithm scores each signal across 7 dimensions: authority, consistency, persistence, relevance, linkage, frequency, differentiation.
14 high-impact anchors
Deploy
Push weighted Brand Memory into each model's retrieval path. Model-specific strategies for ChatGPT, Claude, Perplexity, Gemini.
4-model deployment
Citation Delta
Re-run every prompt at 30/60/90 days. Track citation rate, position, framing. Retainer clients get continuous monitoring.
0% → 81% in 90 days
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. What is your strategy and activation plan for gen AI engine optimization?"
Investing in GEO: How to win — McKinsey →90-Day Measurable Results
Not "wait 6–12 months and hope." Every 30 days, you see exactly which prompts cite your brand — and which don't. The Citation Delta Report is binary: cited or not cited.
Cross-Model Coverage
We deploy across ChatGPT, Claude, Perplexity, and Gemini — each with model-specific reinforcement strategies. One model is a tactic. Four is a moat.
40+ Monitoring Modules
Every client gets access to our proprietary platform. Citation Intelligence, Brand Memory Health, Entity Linkage, Signal Decay Alerts — real-time dashboards for AI visibility.
Performance-Linked Pricing
You pay the full sprint fee only when we hit the agreed citation targets. If we don't deliver, neither do you. Our success is structurally aligned with yours.
Research-Founded, Not SEO Folklore
Founder Bora Kurum has authored 5 books on digital marketing, AI, and SEO. The Adaptive RAG methodology comes from applied research — not recycled SEO tactics with "AI" labels.
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
MeasurementAI models hallucinate when asked about their own output. Asking "do you cite me?" produces fiction — the model invents answers. You cannot audit yourself.
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
ComplexityChatGPT 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.
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
EngineeringAI 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.
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
IntelligenceEven 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.
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
MonitoringWhen 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.
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
PrecisionMore 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.
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
ScaleTesting 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.
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
CostSomeone 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.
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-ProofToday'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.
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.
Traditional SEO vs. Adaptive RAG
Two different games. Two different scoreboards.
| Dimension | Traditional SEO | Adaptive RAG |
|---|---|---|
| Goal | Rank on Google SERP | Get cited in AI model output |
| Measurement | Keyword position, impressions, CTR | Citation Rate, Citation Delta, Cross-Model Persistence |
| Time Horizon | 3–6 months for page 1 movement | 90 days to measured citation lift |
| What's Optimized | Web pages, backlinks, meta tags | Brand Memory, entity relationships, signal weight |
| Target | Google (one engine) | ChatGPT + Claude + Perplexity + Gemini (4+ models) |
| Competitive Moat | Backlink profile, domain authority | Retrieval path engineering, brand memory density |
| Decay Pattern | Slow rank decay if neglected | Can drop to zero overnight (model update) |
| Cost Structure | Monthly retainer for ongoing SEO | Performance-linked sprint + optional retainer |
| Who's Doing It | Every SEO agency | Almost nobody (yet) |
| ROI Visibility | Attribution is murky | Binary: cited or not cited |
Filmfolk: From 0% to 81% Citation Rate in 90 Days
A London-based corporate video production company. Strong SEO. Strong brand. Zero AI visibility. Until RAG Signal.
The Problem
Filmfolk is a premium corporate video production agency in London. Strong SEO (ranking #1–3 for key terms), strong brand, strong portfolio. But when potential buyers asked AI models for recommendations, Filmfolk didn't exist.
- Starting Point: 0% citation rate across all models
- Root Cause: No structured Brand Memory in AI retrieval paths. Competitors with weaker SEO but stronger entity signals were getting cited instead.
- The Stakes: 40% of B2B buyers now use AI tools in their vendor research (Gartner, 2025). Filmfolk was invisible to all of them.
The Results
| Model | Day 0 | Day 30 | Day 60 | Day 90 | Δ |
|---|---|---|---|---|---|
| ChatGPT | 0% | 42% | 71% | 84% | +84pp |
| Perplexity | 0% | 38% | 67% | 86% | +86pp |
| Claude | 0% | 31% | 59% | 78% | +78pp |
| Gemini | 0% | 28% | 52% | 76% | +76pp |
Overall: 0% → 81% Citation Rate. 51 of 63 prompts citing the brand.
"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. That's a completely different kind of visibility. When a CMO asks Claude or ChatGPT 'who should we use for our corporate video,' our name comes up. That's pipeline we weren't even aware we were missing."
— Filmfolk Team, London, UK
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."
"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."
"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."
"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."
"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."
"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."
"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."
"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."
"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."
"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."
"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."
"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."
"Three months. Four models. 78% citation rate. Our competitors are still optimizing meta descriptions. The competitive gap this creates is enormous — and widening."
"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."
"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."
"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."
"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."
"Three months. Four models. 78% citation rate. Our competitors are still optimizing meta descriptions. The competitive gap this creates is enormous — and widening."
"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."
"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."
40+ Modules
Our platform tracks every dimension: Citation Intelligence, Brand Memory Health, Entity Linkage, Competitive Citation Share, Signal Decay Alerts, and 35+ more.
4 LLM Coverage
We don't optimize for one model. ChatGPT, Claude, Perplexity, and Gemini — with Grok and DeepSeek coming. Your Brand Memory deploys across all of them.
Research-Founded
Founder Bora Kurum has authored 5 books on digital marketing, AI, and SEO. The methodology comes from applied research, not SEO folklore.
<24h Response
Every inquiry gets a personal response from Bora within 24 hours. Usually faster. No chatbots, no ticket systems.
Explore Our Research
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.
AI doesn't know you.
It will.
One audit shows you exactly where you stand — across every major AI model your buyers use.
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