Swaran Soft
Large Language Model Optimisation

LLM Optimization ServicesMake Your Brand Visible Across All AI Models

ChatGPT, Gemini, Claude, Llama, Mistral — these are where millions of people are now discovering, evaluating, and choosing brands. Not Google. Not social media. AI models. And if your brand isn't showing up when someone asks those models a question in your space, you're not just missing traffic — you're missing the conversation entirely.

We're a specialist LLM optimization agency. We audit how your brand currently appears across major AI models, pinpoint the gaps in your content authority, and build a structured programme to grow your citation frequency across the LLM ecosystem — not just one model, all of them.

LLM Visibility That Moves the Needle

Real numbers from real programmes. Here's the kind of citation and visibility improvement you can expect from a structured LLM optimization engagement.

5+
Major LLMs covered — ChatGPT, Gemini, Claude, Perplexity, Copilot
3–5×
Increase in brand citation frequency across AI models within 90 days
90 days
Typical timeline to measurable citation frequency improvement across LLMs
ISO 27001
Certified — your content and data handled securely

What Is LLM Optimization?

LLM optimization is the process of aligning your content, brand entity, and authority signals with how large language models actually select sources for their generated responses. It's different from traditional SEO — which targets Google's ranking algorithm — because AI models evaluate sources differently from search engines. They prioritise factual consistency, entity clarity, structured formatting, and breadth of authoritative citation. A standard SEO strategy typically doesn't address any of those things.

Here's why that matters. These models generate answers by drawing on training data and, in the case of RAG systems, live web content pulled in real time. Brands that are consistently authoritative — through structured data, factual depth, knowledge graph presence, and citation-worthy formatting — are much more likely to get referenced in AI-generated responses. The gap between brands investing in LLM optimization and those that aren't is widening fast, because more and more purchasing decisions are starting with an AI query rather than a traditional search.

We cover the full picture: auditing your current AI visibility across all major models, then rebuilding your content architecture around entity clarity, factual authority, and structured schemas. The goal is straightforward — when someone asks any major AI model about your category, your brand gets cited as a trusted source. Getting there takes a methodical, multi-layered approach. Content quality, entity representation, structured data, third-party citation profile — each layer reinforces the others. Together, they create the kind of comprehensive AI authority that gets brands cited consistently, not just occasionally.

Our LLM Optimization Services

We cover every layer of LLM visibility — from multi-model audits and entity disambiguation through to RAG-ready content and the continuous monitoring that keeps your citations growing.

Multi-Model Citation Audit

We test your brand's visibility across ChatGPT, Gemini, Claude, Perplexity, and Copilot — all at once. You get a clear picture of your current citation frequency on each platform, what tone those mentions carry, and which queries your competitors are showing up for while you're not. That's your baseline. Everything we do next is built on top of it.

Entity Disambiguation

AI models need to know, without ambiguity, who you are. We establish your brand, products, executives, and key concepts as clearly defined entities that models can reference with confidence — covering Wikidata presence, knowledge graph entries, and structured entity markup. When models encounter your brand, they should have no doubt about what it is and what it stands for.

RAG-Ready Content Structuring

Most AI models today use retrieval-augmented generation — they pull live web content into their answers in real time. So your content needs to be formatted for that. We reformat and enrich your existing content to be factual, well-structured, source-attributed, and answer-ready. That's what gets pulled into a RAG system and cited, rather than skipped over.

LLM-Specific Schema Implementation

We deploy Schema.org markup chosen specifically to improve machine readability for AI models — Organization, Product, Article, FAQPage, HowTo, and SpeakableSpecification schemas. These aren't just nice-to-haves. They're how you give AI systems explicit, unambiguous signals about what your content means and why it should be cited.

Authority Signal Building

AI models use your backlink profile, brand mention network, and third-party citation footprint as trust signals. We build all of that — through PR placement, authoritative directory listings, and structured citations. The goal is a citation footprint that's broad enough and credible enough that models treat your brand as a reliable source across your industry.

Continuous Model Monitoring

Models change. Citation patterns shift. We track your citation frequency across all major AI platforms on an ongoing basis, alert you when your representation changes, and adjust your content strategy as model behaviours evolve. This is what keeps your AI visibility growing rather than stalling after the initial push.

How Our LLM Optimization Process Works

Four steps, clear milestones. We take you from invisible across AI models to consistently cited — and you'll know exactly where you stand at every stage.

01

LLM Visibility Audit

We start by mapping exactly where your brand stands across ChatGPT, Gemini, Claude, Perplexity, and Copilot. Which queries are you showing up for? Which ones are going to competitors? You need to know both before you can fix either.

02

Entity & Schema Build

We establish your brand entities in knowledge graphs and deploy LLM-optimised schema across your web presence. This is the infrastructure layer — and without it, everything else you do for AI visibility is built on sand.

03

Content Restructuring

We reformat existing content for RAG compatibility and build new authority assets designed specifically to earn AI model citations. Not repurposed blog posts — content built from the ground up for how AI models actually evaluate and select sources.

04

Monitor & Scale

We track citation frequency across all target models every month, expand coverage as new models gain traction, and double down on what's working. Your AI visibility should compound over time — that's the whole point.

Frequently Asked Questions

LLM optimization is the practice of making your brand, content, and authority signals visible and credible to large language models like ChatGPT, Gemini, and Claude. It matters because hundreds of millions of people are now using AI assistants as their primary way to find information, compare options, and make decisions. If your brand isn't being cited by these models, you're invisible to a segment of high-intent users that's growing fast — and the gap between brands that invest in this and those that don't is already widening.

Start Your LLM Visibility Program

Whether you're focused on ChatGPT, Gemini, Claude, or the full AI ecosystem, we build the content authority and entity signals that get your brand into those answers. Start with a visibility audit — we'll show you exactly where you stand and what it'll take to improve.

Free AI Visibility Audit

Ready to Appear in AI Answers?

Book a free AI Visibility Audit. We'll show you exactly where your brand appears (and disappears) across ChatGPT, Perplexity, Gemini, and Google AI Overviews — then build a plan to fix it.

No vendor lock-in
Data stays in India
Results in 90 days
ISO 9001 certified