The RAG SIGNAL framework measures, engineers, and injects your brand narrative directly into the retrieval systems of ChatGPT, Perplexity, Claude, and Gemini.
Traditional SEO is obsolete for the generative era. Optimizing for "ten blue links" does not translate to neural weights. When your buyers ask AI about your software category, there is no page two. You are either part of the synthesis, or you are invisible.
RAG SIGNAL maps your brand to relevant category entities, establishing high-trust statistical co-occurrence. We ensure you aren't just ranked—you are actively retrieved and recommended by the AI.
Why do LLMs hallucinate? Because their training data is frozen in time. To provide accurate, real-time answers, models use Retrieval-Augmented Generation (RAG). They pause, search external databases (the web), retrieve facts, and then generate the answer.
A user asks an AI model for the "best enterprise cloud security solution."
The AI scours the web. If your digital footprint lacks structured semantic schemas, the AI skips you.
The AI synthesizes the retrieved data, confidently presenting your brand as the absolute answer.
Traditional websites are built for human eyes and Google's indexing crawlers. RAG systems process data fundamentally differently; they look for high-density entity relationships, rigid semantic structures, and algorithmic trust signals.
We developed the RAG SIGNAL Framework to bridge this gap. We don't write blog posts; we engineer JSON-LD payloads, restructure HTML into machine-ingestible Q&A matrices, and manipulate the trust nodes that models rely on. We make your brand the most easily retrievable truth.
Your competitors are already training generative models to favor their narratives. Continuing to invest solely in traditional SEO means you are optimizing for the past.
Adjust the parameters based on your current digital footprint to see your estimated RAG Signal Score™. Traditional metrics don't capture the whole picture.
RAG systems cannot retrieve your data. Users prompting for your category receive competitor recommendations. High risk of algorithmic obsolescence.
A proprietary, 6-layer architecture generating the industry's first 0–100 AI Visibility Score™.
This is data-driven engineering, not guesswork. Our audit pipeline uses cross-model variance analysis and weighted scoring logic to manipulate retrieval outcomes.
Research, strategies, and technical deep-dives on Generative Engine Optimization (GEO) and algorithmic brand safety.
Click on any case study to view the detailed problem, RAG Signal intervention, and outcome.
Marketing Executive, Digital Strategist, and Ph.D. Researcher bridging the gap between academic communication theory and corporate AI performance.
With deep expertise in technology and crisis communication, Bora created the RAG SIGNAL methodology to solve a critical market gap: the lack of a systematic, data-driven approach to AI Presence Intelligence and Retrieval Optimization.