Every AI platform plays by different rules. ChatGPT doesn't select sources the same way Perplexity does. Gemini works nothing like Claude. Yet most businesses apply an identical strategy everywhere, or worse, apply none at all.
This hub brings together our dedicated guides for each major AI platform. For each one, we detail how it works, what criteria it uses to select sources, and the concrete actions to get cited. The goal is straightforward: give you a strategy adapted to each answer engine, not a generic copy-paste approach.
In 2026, B2B companies visible on only one AI platform are missing 60 to 70% of their potential audience. Multi-LLM visibility is no longer a luxury. It's an operational necessity.
Why a multi-platform strategy is essential
The generative AI market is fragmented. No single platform holds more than 35% market share. ChatGPT dominates in volume, but Perplexity captures high-intent searches, Gemini is integrated into the Google ecosystem, and Copilot reaches the entire Microsoft 365 user base.
Each platform has its own citation biases. ChatGPT favors high-authority English-language sources. Perplexity prioritizes freshness and cites with direct links. Gemini relies on Google's Knowledge Graph. Claude values nuanced, well-structured content. Ignoring these differences means optimizing blind.
A multi-platform strategy doesn't mean multiplying your workload tenfold. 70% of optimizations are universal: content structure, Schema.org markup, topical authority. The remaining 30% are platform-specific adjustments. That's exactly what our guides detail.
At AISOS, we measure our clients' visibility across the 10 major AI platforms every month. The data shows that companies adopting a multi-LLM approach see their AI Visibility Score progress 2.5x faster than those focusing on a single platform.
Comparison of the 10 major AI platforms
| Platform | Company | Type | Cites sources? | Web access |
|---|---|---|---|---|
| ChatGPT | OpenAI | Chat + search | Yes (search mode) | Yes (browsing) |
| Perplexity | Perplexity AI | Answer engine | Always, with links | Yes (native) |
| Gemini | Chat + Google integration | Yes (with links) | Yes (Google Search) | |
| Claude | Anthropic | Advanced chat | Via knowledge | Web search |
| Copilot | Microsoft | Chat + Bing search | Yes (with Bing links) | Yes (Bing) |
| Meta AI | Meta | Social chat | Sometimes (Bing/Google) | Yes (via partners) |
| Mistral | Mistral AI | Chat + Le Chat | Yes (search mode) | Yes (Brave Search) |
| AI Overviews | SERP-integrated answer | Yes (Google links) | Native Google Search | |
| SearchGPT | OpenAI | AI search engine | Always, with links | Yes (native) |
| DeepSeek | DeepSeek | Chat + search | Yes (search mode) | Yes |
This table captures the fundamental differences, but behind each line is an ecosystem with its own indexing rules, selection biases, and specific opportunities. Explore each guide for the details.
Platform guides
Each guide below is a dedicated operational mini-manual for a specific platform. You'll find the internal workings of the LLM, its source selection criteria, and concrete actions to implement.
- How to Rank on ChatGPT: the market leader with 200+ million weekly users
- How to Rank on Perplexity: the answer engine that always cites its sources
- How to Rank on Gemini: Google's AI, integrated into the entire ecosystem
- How to Rank on Claude: Anthropic's AI, known for precision
- How to Rank on Copilot: Microsoft's AI, integrated into Office 365 and Bing
- How to Rank on Meta AI: Meta's AI, present on WhatsApp, Instagram, and Facebook
- How to Rank on Mistral: the French champion of generative AI
- How to Rank on AI Overviews: AI answers directly in Google search results
- How to Rank on SearchGPT: OpenAI's search engine
- How to Rank on DeepSeek: the Chinese outsider on the rise
The universal optimization foundation for all LLMs
Before diving into platform-specific tactics, here are the fundamentals that work everywhere.
Content structure. All LLMs prefer well-structured content with hierarchical headers (H1, H2, H3), bullet points, tables, and short paragraphs. Content that's easy to parse is content that's easy to cite.
Schema.org markup. FAQPage, HowTo, Article, Organization, Product: these schemas are read by the majority of RAG systems. They constitute a universal trust signal.
Topical authority. Build a content cluster around your expertise rather than isolated articles. LLMs evaluate your authority on a topic, not on a single page.
Fresh, sourced data. Date your content, cite your sources, update regularly. RAG systems penalize undated content or content with obsolete figures.
Complete About page. Your "About" page is often the first page LLMs consult to validate your entity. Include founders, company history, key metrics, and full Organization schema.
These five fundamentals represent 70% of the effort. The remaining 30% are platform-specific optimizations you'll find in our dedicated guides.
How AISOS supports you across every platform
Our multi-LLM approach follows three steps.
1. Multi-platform audit. We test your visibility across all 10 major platforms with 20 key queries from your industry. The result: an AI Visibility Score per platform and a global score, with identification of priority gaps.
2. Targeted optimization. Based on the audit, we deploy universal optimizations (structure, schema, authority) then platform-specific adjustments where your potential is highest. No spray-and-pray: we concentrate effort where impact is maximal.
3. Continuous monitoring. Every month, we measure your visibility evolution across every platform, detect regressions, and adjust the strategy. LLMs evolve fast: an optimization that worked in January can become obsolete by March.
The Essentials plan (490 euros/month) covers multi-platform audit and monitoring. The Growth plan (990 euros/month) adds optimized content creation and mention strategy to accelerate your progress. In both cases, you know exactly where you stand on each platform, every month.
FAQ: Multi-platform AI visibility
Should I optimize for all platforms simultaneously?
No. Start with the 3 platforms where your audience is most present. For B2B, that's typically ChatGPT, Perplexity, and Gemini. Add others progressively once the fundamentals are in place.
Can optimizations for one platform hurt on another?
Very rarely. 95% of optimizations are positive or neutral across all platforms. The rare exceptions involve very specific formats (like Perplexity's list preferences) that simply have no effect elsewhere, with no negative impact.
How long before seeing results?
Initial improvements are visible within 4-6 weeks on RAG platforms (Perplexity, Gemini, SearchGPT). For platforms that rely on training data (ChatGPT without browsing, Claude), the impact is slower, typically 3-6 months.
How do you measure visibility on each platform?
We use a protocol of 20 industry queries tested monthly on each platform. For each query, we measure: presence in the response, citation position, sentiment (positive/neutral/negative), and presence of a link to the client's site.