Track your brand’s visibility in AI answers - before others take your place.
People don’t search anymore. They ask.
AI answers are establishing the new market defaults right now.
If you aren't visible here, you are being replaced.
User Prompt
Real questions asked to AI models about your category (e.g., "Best CRM for startups").
Model Response
GPT, Claude, and Gemini generate answers in real-time, forming new user habits.
Visibility Signal
We structure the answer into data: your Share of Voice vs. competitors.
The complexity of tracking LLMs.
Fluid Rankings
Unlike a Google search, LLMs give different answers depending on prompt phrasing, context window, and stochastic variance. A single test query tells you nothing. We run persistent statistical sampling.
Silent Updates
OpenAI, Google, Anthropic update models silently. Yesterday's leading position disappears overnight without a changelog. We detect model drift instantly and visualize the fallout.
Unstructured Data
LLMs output raw paragraphs, lists, and prose. Extracting robust Share of Voice metrics requires secondary NLP extraction pipelines designed specifically to benchmark brand mentions against competitors.
Unified Integration
OpenAI, Anthropic, and Google all use completely different API structures and message formats. We standardize the integration so you can seamlessly query and compare your brand across all ecosystem leaders.
The Early Window
Search engines gave you a rank. You knew if you were #1 or #10. You could measure it, track it, and optimize for it.
LLMs are becoming monetized, competitive surfaces.
ChatGPT is testing ads. Claude is becoming a primary interface. When a user asks for a recommendation, the "default" answers are being established now. Late entry means competing against entrenched perception.
Context & Documentation
LLMO is no longer optional for growth teams.
AI assistants are now a discovery layer. Users ask models directly, and recommendations are shaped by model behavior, citations, and prompt context.
That means visibility is dynamic. Brand presence can change by model, query, and update cycle. Tracking this continuously is the core LLMO advantage.
Why Teams Invest in LLMO
- 1. Detect when your brand is absent from high-intent AI answers.
- 2. Compare citation and recommendation share against competitors.
- 3. Track model drift before it impacts pipeline and revenue.
- 4. Build an optimization loop from prompts to measurable visibility outcomes.
Simulate
BrandIndex acts as a real user. We fire persistent, randomized queries at models like GPT-5.2, Claude 4.7, and Gemini 3 to reproduce exactly what your customers see.
Detect
Our engine reveals the truth. We parse the output to identify if your brand was mentioned, if it was recommended, or if a competitor has taken your spot.
Quantify
We turn text into data. Track your 'Share of Voice' over time. See how model updates affect your visibility. You can't influence what you can't see.
Automate
Set it and forget it. Schedule daily, weekly, or monthly automations to continuously benchmark your visibility across all major AI models without lifting a finger.