Stay Ahead — Make Your Brand AI Trusted on Gemini, ChatGPT, Claude, DeepSeek and other AI search platforms
In the era of generative search, traditional SEO is no longer enough. With our proprietary FLOWS Brand Trust Model, continuously quantify, monitor, and improve your brand's "Trust Index" in AI models, seizing traffic in the AI era.
{ "source": "google_search", "query": "best coffee machine" }
{ "source": "reddit", "sentiment": "positive", "brand": "Brand A" }
{ "source": "youtube_transcript", "context": "extraction_quality" }
> analyzing_intent...
Trust Score
Brand A Pro
Trusted by Leading Brands
Supported AI Platforms
Core Methodology
FLOWS Brand Trust Model
An LLM‑powered brand equity evaluation system that distills real‑world feedback from the AI industry into professional dashboards, giving you a clear, data‑driven view of how your brand is actually performing.
AI Optimization Insight
Current analysis shows excellent performance in Leading Orientation (LO), but room for growth in Origin Verification (OV). Improving source authority is expected to boost the overall score by about 5%.
Find-ability Index
Frequency of brand mentions in AI responses, position weight, and overall length proportion.
Leading Orientation
Degree of recommendation in AI responses, plus informativeness and intent matching.
Origin Verification
Authority, credibility, and traceability coverage of brand information sources in AI responses.
Website Structure
AI-friendliness of brand websites and content carriers, and technical infrastructure completeness.
Spread Index
The spread and distribution of the brand in public information environments like search engines and vertical platforms.
Full-Link Intent Simulation Engine
Unlike traditional SEO analyzing single keywords, we built an intelligent simulation system powered by our proprietary question generation model. It simulates thousands of real users asking questions to major AI platforms, capturing brand performance in AI responses in real-time. Brands can also customize the simulation engine for periodic monitoring based on their content optimization cycles, discovering patterns in AI preferences to enhance brand trust.
01. Global Data Collection
Build Brand Exclusive Knowledge Graph
02. Intent Abstraction
AI Reverse Inference of User Real Needs Scenarios.
03. Simulation Q&A
Simulate 10,000+ user questions to LLMs across various AI platforms and scenarios, capturing real brand feedback and performance under different intents and AI models.
04. FLOWS Scoring & Attribution
Generate a 5-dimensional radar chart to pinpoint shortfalls in content (WS) or recommendation (LO), and auto-generate repair strategies.
Invisible AI Traffic,
Visible on Dashboard
Manage your AI brand assets like Google Search Console. Monitor Mention Rate and Sentiment in real-time.
Driven by "Taste" features
Scenario Ranking Trend
Optimization Required (Critical)
DeepSeek model's recommendation weight for Brand A in "Fully Automatic Coffee Machine" scenario dropped by 15%. Main reason involves high-weight citation of a recent review article.
Generate Fix ContentTop Generated Questions
Latest Insights
AI marketing strategies, GEO optimization guides, and brand visibility insights.
How Much Do AI Crawlers Take—and How Many Visitors Do They Send Back?
Crawl-to-Referral Ratio can diagnose the exchange between AI crawling and human return traffic. It is not yet a standardized industry metric, a search ranking factor, or a complete measure of GEO ROI.
Sep 28, 2026
Web Pages Do Not Enter AI Context Whole: How Filters Vital, Irrelevant, and Duplicate Spans
In March 2026, Perplexity described a new extraction and evaluation pipeline for its Search API. For each query-document pair, the system labels spans as vital evidence, several forms of irrelevant content, duplicates, and other categories. Two months later, Perplexity published the production design behind its query-aware context compression model, explaining how those granular labels become smaller snippets in its applications and API Platform.
Sep 21, 2026
Why Does AI Cite You? Bing Grounding Queries Reveal the Retrieval Layer
Microsoft is beginning to expose an earlier part of that chain. In February 2026, Bing Webmaster Tools launched AI Performance in public preview, showing citations, cited pages, and grounding queries across Microsoft Copilot, AI-generated summaries in Bing, and selected partner integrations. Microsoft Clarity made Citations generally available in May and added Query Topics in August to group large sets of grounding queries into themes
Sep 17, 2026