QUESTIONS
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RAG Signal is a done-for-you services engagement. We audit, build, and maintain the systems that drive AI visibility — across entity signals, source weighting, and curated brand knowledge bases. Clients receive execution, measurement, and strategic guidance. You also get access to our tracking platform as part of the engagement.

RAG Signal was founded by Bora Kurum, a marketing practitioner and Ph.D. researcher at Istanbul Bilgi University. His academic work focuses on communication science, LLM retrieval behavior, and how brands are represented inside generative AI systems. Read more about Bora →

Adaptive RAG is our proprietary framework that goes beyond static knowledge injection. We continuously adjust which sources enter the AI retrieval layer, how they are weighted, how fresh they are, and how consistently they reinforce your brand's entity signals. The system adapts to model behavior, competitor pressure, and prompt patterns — so your brand stays retrievable as AI systems evolve.

Traditional SEO optimizes for Google rankings and clicks. RAG Signal optimizes for AI citations and brand mentions in AI-generated answers. These are different retrieval systems with different signals. Strong Google rankings do not translate to AI presence — Filmfolk had both, but only after the Adaptive RAG sprint. See the comparison table →

A curated brand KB is a structured, weighted collection of facts, entities, and proof points about your brand that we build and maintain. It's the foundation of the Adaptive RAG system — it ensures the right information about your brand is retrievable, weighted correctly, and kept fresh over time.

Most clients see measurable citation improvements within the 90-day sprint. AI systems update continuously, so progress compounds over time as authority and clarity signals strengthen. We track the same prompt set before and after, so the delta is always measurable.

AI visibility growth refers to measurable changes in: how often your brand is mentioned or cited in AI answers; whether your company is included in comparison and recommendation prompts; and how accurately AI systems describe your services and positioning. We track these signals directly across generative platforms — not rankings or website traffic.

Yes. Filmfolk went from 0% to 81% AI citation rate (51/63 tracked prompts) after the 90-day sprint. The case study includes real before/after prompt outputs and verified client attribution. Read the full case study →

The AI Presence Audit is free (by application). The 90-Day Adaptive RAG Sprint is €499 upfront + €899 when retrieval targets are met. The monthly retainer is €599/month on a 12-month contract. See full service details →

The €899 second payment on the 90-Day Sprint is only due when agreed retrieval targets are met. We define the targets upfront and only invoice when they're achieved. We have skin in the game on every engagement.

This is not a fit for companies looking for quick SEO fixes or keyword ranking boosts, paid ads management, or automated AI tools without human analysis. Our work is designed for B2B companies focused on long-term AI visibility, credibility, and recommendations inside AI-driven buyer research.

Our work is designed to improve how your brand appears inside ChatGPT, Google Gemini / AI Overviews, Perplexity, Claude, Grok, and more. We optimize for the shared signals these systems use to understand businesses, compare vendors, and generate recommendations.

You can attempt it yourself, but Adaptive RAG requires continuous prompt testing, source weighting, entity mapping, and model behavior tracking. Most companies lack the time, tools, and expertise to do this consistently. We provide the execution, measurement, and strategic guidance as a done-for-you service.

Being mentioned occasionally is not the same as being cited consistently. We measure citation rate across a full prompt set—not cherry-picked examples. If you're at 20-30% citation rate, there's significant room for improvement. We also track accuracy: is AI describing your services correctly?

We measure citation delta: the change in citation rate before and after the sprint. We test the same prompt set (typically 40-80 prompts) across all major AI models and calculate the percentage of prompts where your brand is cited. We also track per-model performance and citation accuracy.

We work with B2B service companies, SaaS platforms, agencies, consultancies, and professional services firms. Our clients range from video production (Filmfolk) to energy consulting (UEC Energy) to manufacturing (Benoplast). If buyers research your category in AI, we can help.

llms.txt is an emerging standard for providing structured information to AI systems. It's similar to robots.txt but for LLMs. We recommend it for all clients as part of the Brand Memory build. It helps AI systems understand your brand, services, and key facts in a machine-readable format.

We use AI as a research and analysis tool, but all strategic decisions, entity mapping, and source weighting are done by humans. Brand Memory construction requires editorial judgment, not automated content generation. We prioritize quality and accuracy over volume.

Adaptive RAG and traditional SEO are complementary but distinct. Our work focuses on entity clarity, structured data, and source authority—signals that can indirectly benefit SEO. However, our primary goal is AI citation rate, not Google rankings. Most clients maintain or improve their SEO while gaining AI visibility.

Entity confidence score measures how clearly and consistently your brand is represented across weighted sources. A high score means AI systems can confidently identify who you are, what you do, and why you're relevant. A low score means your entity signals are weak, conflicting, or missing.

AI models update continuously, but the frequency varies by platform. ChatGPT and Perplexity pull real-time web data. Claude and Gemini have periodic knowledge cutoffs but also use retrieval. This is why freshness management is critical—stale signals hurt citation rates.

We cannot guarantee 100% citation rate—no one can. AI models are probabilistic systems. However, we do guarantee measurable improvement. The €1099 second payment on the 90-Day Sprint is only due when agreed retrieval targets are met. We define realistic targets based on your baseline audit.

We test 15-25 real buyer prompts across ChatGPT, Claude, Perplexity, and Gemini. We identify where your brand is missing, who's winning instead, and what the signal gaps are. You receive a written report with before/after examples and a recommended action plan. No commitment required.

The audit takes 5-7 business days from approval. We need time to research your category, map competitors, design the prompt set, and run the tests across all models. Rush audits are available for an additional fee.

For the audit: your website URL, a brief description of your services, and 3-5 competitors. For the sprint: access to your website (for schema/llms.txt implementation), brand assets, and a list of key facts you want AI to know about your company. We handle the rest.

Yes. We work with clients worldwide. Our current portfolio includes companies in the UK, Turkey, UAE, Philippines, and more. AI visibility is a global challenge. We optimize for English-language AI systems but can adapt for multilingual brands.