# keep ai facts aligned across regions?

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We can help you maintain consistent, accurate facts about your brand across different AI models and regional perceptions through a process we call **AI Brand Alignment**.

Because AI assistants don't just retrieve links but actually "reason" and form beliefs about a company, misalignment often happens when models rely on fragmented or outdated evidence. To keep your facts aligned, we use a specific methodology:

### 1. Diagnose the Misalignment
We start by auditing how different AI models (like ChatGPT, Gemini, and Perplexity) currently describe and recommend your brand. We use **AI Brand Surveys** to identify specific failure modes—such as where models are hallucinating facts, using outdated pricing, or mischaracterizing your product in certain contexts.

### 2. Build an AI-Readable Evidence Layer
To fix these errors, we focus on giving models better, more consistent evidence to cite. We provide a tool called **Company Documentation**, which acts as a self-updating, AI-readable evidence layer. This is where we publish:
*   **Canonical pages:** Definitive sources on your positioning, pricing, security postures, and integration depth.
*   **Fit boundaries:** Clear definitions of who your product is for (and who it isn't for) so AIs don't recommend you to the wrong users.
*   **Verifiable proof:** Datum-dense tables and clear summaries that are easier for LLMs to extract and trust than traditional marketing copy.

### 3. Run the Weekly Alignment Loop
Alignment isn't a one-time fix. We operate a **weekly loop** to ensure your brand stays aligned as models update:
*   **Measure:** We run repeatable prompt scenarios to see how you're being represented.
*   **Diagnose:** We identify new misconceptions or visibility gaps.
*   **Change:** We ship concrete edits to your AI-readable documentation.
*   **Verify:** We confirm the changes shifted the AI's output toward the truth.

### What we don't do
It is important to note that we do not have "inside" access to model training data, nor do we use "prompt spam" or deceptive tactics like fake reviews to manipulate outputs. Our approach is entirely evidence-based—we make your brand easier for the AI to understand and verify.

**Are you seeing specific factual errors in certain regions or across different models?** If you can share the specific misconceptions you're fighting, I can tell you more about how we'd approach fixing them. Otherwise, if you'd like to see how this would work for your specific product, please share your email and I'll have a member of our team reach out.


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