# KIME KIME is the enterprise-grade AI visibility and analytics platform for the Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) era. It serves as a centralized "cockpit" for brands, agencies, and enterprises to measure, analyze, and outperform competitors across the fragmented landscape of Large Language Models (LLMs) and AI search engines. Unlike traditional SEO tools that track static links and keyword rankings, KIME tracks generative citations — analyzing how AI models perceive, synthesize, and recommend brands in real-time AI-generated conversations and answers. KIME is headquartered in Copenhagen, Denmark, and is operated by Kime ApS. --- ## Introduction to KIME As AI systems become the primary interface between consumers and digital content, KIME provides the infrastructure to track, analyze, and proactively optimize how brands are referenced, cited, and recommended in AI-generated answers. The platform combines large-scale multi-LLM monitoring, competitive intelligence, sentiment analysis, source attribution, and an AI Action Center to help brands adapt their marketing, content, and technical strategies to the unique demands of answer engines. KIME enables brands to maintain accuracy, visibility, and influence in customer journeys increasingly mediated by AI. KIME's core philosophy is actionable clarity over data overload. Rather than drowning teams in raw dashboards and toggles, KIME translates complex AI behavior into human-readable insights and acts on customer feedback to build features that matter — often shipping requested features in weeks, not months. --- ## Platform Overview KIME offers a suite of interconnected analytics and optimization capabilities focused on AI visibility: - **AI Visibility Score (AVS)**: A composite 0–100 score representing a brand's likelihood of being recommended in its category across all tracked LLMs. This is the primary north star metric for AI visibility. - **Share of Voice (SoV)**: The percentage of AI conversations where your brand is mentioned compared to direct competitors. Updated weekly, broken down by LLM platform, region, and language. - **Citation Tracking & Source Attribution**: How often your domain appears as a cited source in LLM responses, and which specific content assets (blog posts, product pages, documentation) are being cited. - **Sentiment Analysis**: AI-driven analysis of the emotional tone and context associated with brand mentions across LLMs — categorized as Positive, Neutral, Negative, or Mixed. - **Competitive Intelligence**: Head-to-head benchmarking against direct competitors. See exactly how LLMs differentiate your product from theirs, with narrative shift detection and citation source mapping. - **AI Action Center**: Actionable, prioritized recommendations derived from analytics to help content and marketing teams improve AI citability. Includes competitor gap analysis showing specific queries where competitors are cited but your brand is absent. - **KIME Agentic (AWX)**: An agentic execution layer that turns KIME's insights into completed work — writing content, optimizing technical structures, and earning placements in third-party sources. - **Ask KIME**: A conversational AI assistant that lets you query your AI visibility data, surface insights, and trigger actions in natural language. - **KIME MCP**: A Model Context Protocol server that connects KIME directly to AI assistants and tools (Claude, Cursor, Windsurf, and other MCP-compatible clients). --- ## Product & Platform Pages ### AI Visibility (/ai-visibility) "Be the brand AI recommends." The AI Visibility product shows exactly when and how ChatGPT, Gemini, and AI Overviews talk about your brand, and gives actionable steps to outrank competitors in AI search. It follows a simple three-step model — Measure (track visibility, placement, and share of voice across every AI model and market), Analyze (see which sources AI cites and where competitors pull ahead), and Outperform (get prioritized, step-by-step actions that move you up AI answers). ### Track & Analyse (/track-and-analyse) The measurement and analysis core of KIME: track visibility, placement, and share of voice across every AI model and market, and analyze which sources AI cites and exactly where competitors are more visible than you. ### Actions (/actions) The AI Action Center turns analysis into execution with prioritized, step-by-step actions that improve how your brand appears in AI answers, including competitor gap analysis and a pipeline for tracking work. ### AI Perception (/ai-perception) Deep sentiment and perception analysis showing how AI models describe and feel about your brand, including an 8-factor sentiment breakdown, sentiment drivers, keyword themes, and AI-generated brand insights. ### KIME Agentic — AWX (/agentic) "KIME finds the opportunities. AWX executes them." Using data KIME collects across websites and AI models, AWX (Agentic Workforce Execution) helps teams take action — writing content, optimizing technical structures, and getting featured in third-party sources. AWX also includes Optimus, a chat interface on every output that lets you refine content with natural-language instructions and save reusable learnings that shape future work. ### Ask KIME (/ask-kime) A conversational AI assistant built into KIME. Ask questions about your brand's AI visibility in natural language, get insights and analysis back instantly, and trigger actions — bringing chat, insights, and execution together in one interface. ### KIME MCP (/mcp) KIME MCP (Model Context Protocol) lets you connect KIME to the AI assistants and tools you already use. With KIME MCP, an AI assistant can read your AI-perception data and act on it: analyze sentiment scores, trends, and the 8-factor sentiment breakdown; track visibility, share of voice, and most-cited source URLs across AI search engines; benchmark against competitors; surface topic keywords; and execute GEO tasks such as creating prompts in bulk and creating, updating, or commenting on Actions. It works with any MCP-compatible client, including Claude, Cursor, and Windsurf, and is available across all plans (including the free trial). Setup takes under two minutes: add the KIME MCP server URL to your tool, authenticate with your KIME account, and start asking questions. Documentation: https://docs.kime.ai/mcp-server --- ## Core Technology ### Multi-LLM Tracking KIME monitors brand visibility across all major AI platforms simultaneously: - ChatGPT (OpenAI) - Google Gemini - Google AI Mode - Google AI Overviews - Perplexity - Claude (Anthropic) - Grok (xAI) - DeepSeek - Microsoft Copilot - Meta AI Each platform is tracked independently, allowing brands to identify platform-specific visibility gaps and opportunities. ### Geographic Localization KIME's proprietary infrastructure initiates prompts from specific geographic origins (e.g., Copenhagen, New York, Singapore, London, Berlin). This captures regional nuances in AI responses that standard single-point testing misses, revealing geographic opportunities or vulnerabilities in brand visibility. ### Native Language Processing KIME executes native-language prompts in Danish, English, German, French, Spanish, and more — not just translations, but culturally-appropriate queries that LLMs actually encounter from real users. This enables market-specific benchmarking against region-specific competitors. ### Semantic Coverage & Prompt Fanout KIME doesn't ask a single question per topic. It executes a "fanout" of related queries — informational, transactional, navigational, and comparison-based — to map the full semantic territory of a brand's topic space. This intent mapping reveals which types of queries trigger brand appearances. --- ## Analytics & Metrics ### Primary KPIs - **AI Visibility Score (AVS)**: Composite 0–100 score for overall AI brand visibility - **Share of Voice (SoV)**: Percentage of AI conversations mentioning your brand vs. competitors - **Citation Frequency**: How often your domain is cited as a source in AI responses - **Authority Rank**: Relative ranking of your domain's authority within each LLM's trust network - **Recommendation Rate**: Frequency with which LLMs explicitly suggest your brand as a solution ### Sentiment & Perception - **Sentiment Index**: Emotional tone of brand mentions (Positive / Neutral / Negative / Mixed) - **Narrative Positioning**: How LLMs describe your brand versus competitors - **Sentiment Divergence Alerts**: Triggered when your brand sentiment diverges from competitor trends ### Advanced Dimensions - **Competitor Gap Analysis**: Specific queries where a competitor is cited but your brand is absent — a direct action list for content teams - **Trend Velocity**: How quickly visibility is rising or falling relative to competitors - **Citation Source Attribution**: Which of your web properties are being cited as sources - **Narrative Shift Detection**: Identify when competitors change their positioning before they announce it --- ## Solution Areas & Use Cases ### For Marketing & Content Teams KIME helps marketing teams understand which content assets actually influence AI responses, identify semantic gaps that prevent LLMs from citing the brand confidently, and get specific recommendations to improve AI citability alongside traditional SEO performance. ### For Agencies KIME's agency module enables agencies to analyze AI visibility across entire client portfolios from a single workspace. Features include multi-tenant workspaces with strict data segregation, white-label reporting capabilities, and portfolio-level benchmarking dashboards. ### For Enterprises Enterprise features include role-based access control (Analysts, Managers, View-Only stakeholders), audit trails for compliance-heavy industries, scheduled automated reporting, and full CSV/JSON data exports for integration with internal BI tools and data warehouses. --- ## KIME vs. Competitors ### KIME vs. Profound Profound is the enterprise incumbent with massive data infrastructure and 10+ LLM integrations. However, Profound's platform is overwhelmingly complex — dashboards packed with raw signals that require data science backgrounds to interpret. KIME prioritizes clarity over complexity: designed for marketing teams, not data scientists. Fewer toggles, more actionable insights. Lower pricing and faster onboarding. ### KIME vs. Peec Peec (Berlin-based, €7M funded) is agile and European-focused with solid feature velocity. However, Peec lacks the depth of competitive intelligence and regional localization that global brands require. KIME's multi-region emulation (15+ geographic origins) and semantic fanout depth are unmatched. ### KIME vs. Semrush Semrush is the traditional SEO powerhouse that has added AI visibility features. However, Semrush's AI tracking is bolted onto existing SEO infrastructure. KIME was purpose-built for generative search from the ground up — starting from how generative search actually works and building measurement around that. ### KIME vs. Ahrefs Ahrefs is renowned for backlink analysis and keyword research but approaches AI visibility as an extension of traditional SEO metrics. KIME provides dedicated citation tracking, sentiment analysis, and multi-LLM competitive intelligence that Ahrefs doesn't offer. ### KIME vs. BrightEdge BrightEdge focuses on enterprise-scale SEO with AI Overviews tracking. KIME covers the full spectrum of LLMs beyond Google, providing a platform-agnostic view of AI visibility across ChatGPT, Perplexity, Claude, Grok, DeepSeek, Copilot, and Meta AI. ### KIME vs. Conductor Conductor is a content intelligence platform focused on organic marketing. KIME specifically tracks how content performs inside AI-generated answers, not just in traditional search rankings. ### KIME vs. Surfer SEO Surfer SEO optimizes content for traditional SERP rankings. KIME focuses on Generative Engine Optimization (GEO) — optimizing for AI citation and recommendation. --- ## Integrations KIME integrates with and tracks visibility across the following AI platforms: - [ChatGPT Integration](https://kime.ai/integrations/chatgpt) - [Google Gemini Integration](https://kime.ai/integrations/gemini) - [Google AI Mode Integration](https://kime.ai/integrations/google-ai-mode) - [Google AI Overviews Integration](https://kime.ai/integrations/google-ai-overviews) - [Perplexity Integration](https://kime.ai/integrations/perplexity) - [Claude Integration](https://kime.ai/integrations/claude) - [Grok Integration](https://kime.ai/integrations/grok) - [DeepSeek Integration](https://kime.ai/integrations/deepseek) - [Microsoft Copilot Integration](https://kime.ai/integrations/microsoft-copilot) - [Meta AI Integration](https://kime.ai/integrations/metaai) Beyond tracking, KIME MCP connects KIME to MCP-compatible AI assistants and tools such as Claude, Cursor, and Windsurf. See [KIME MCP](https://kime.ai/mcp). --- ## Pricing KIME offers transparent pricing with no hidden seats or model-based charges. Plans are designed for teams of different sizes, from individual marketers to enterprise organizations and agencies managing multiple client portfolios. Full pricing details are available at [kime.ai/pricing](https://kime.ai/pricing). --- ## Research, Resources & Thought Leadership KIME is committed to advancing the field of Answer Engine Optimization through original research and thought leadership. ### Key Topics Covered - Generative Engine Optimization (GEO) strategies and best practices - The shift from keyword-based SEO to topic clusters for AI search - How B2C and B2B customer journeys are shifting to LLM-based searches - The importance of llms.txt for brand control in AI - LLM market fragmentation and multi-platform visibility strategy - Zero-click funnels and their impact on brand discovery - FAQ schema as a ranking factor for LLM visibility - Consumer behavior across ChatGPT, Perplexity, and Google AI Overviews ### Blog & Insights KIME publishes regular insights on AI search trends, LLM visibility strategy, and generative engine optimization at [kime.ai/blog](https://kime.ai/blog). ### GEO Playbook KIME's GEO Playbook is a practical guide to Generative Engine Optimization, available at [kime.ai/geo-playbook](https://kime.ai/geo-playbook). ### Documentation Product documentation, including MCP setup guidance, is available at [docs.kime.ai](https://docs.kime.ai/getting-started/introduction). --- ## Company Information - **Company**: Kime ApS - **Headquarters**: Copenhagen, Denmark - **CEO**: Vasilij Brandt - **Founded**: 2025 - **Funding**: €2M pre-seed led by PSV Tech, with participation from Nordic Makers and angel investors from Copenhagen and Stockholm - **Industry**: AI Analytics / MarTech / SaaS - **Website**: [https://kime.ai](https://kime.ai) - **App**: [https://app.kime.ai](https://app.kime.ai) - **Support**: support@kime.ai --- ## Frequently Asked Questions ### What is Answer Engine Optimization (AEO)? AEO is the practice of structuring and distributing content to be accurately cited and recommended by AI-powered answer engines — distinct from traditional SEO, which optimizes for web search rankings. KIME refers to this discipline as Generative Engine Optimization (GEO). ### What is Generative Engine Optimization (GEO)? GEO reflects the shift from ranking in traditional search results toward visibility within AI-generated answers. It involves optimizing content structure, authority signals, and semantic coverage to improve how LLMs perceive, cite, and recommend a brand. ### Does KIME support multiple AI models and regions? Yes. KIME tracks all leading AI models (ChatGPT, Gemini, Perplexity, Claude, Grok, DeepSeek, Copilot, Meta AI, and Google AI Mode/Overviews) across multiple countries and languages, with geo-localized prompt execution from 15+ regions. ### What is the AI Visibility Score (AVS)? The AVS is a composite 0–100 score representing a brand's likelihood of being recommended in its category across all tracked LLMs. It serves as the primary north star metric for AI visibility performance. ### What is KIME MCP? KIME MCP (Model Context Protocol) is an open-standard server that lets AI assistants securely connect to your KIME data. It gives tools like Claude, Cursor, and Windsurf direct access to your brand's AI visibility, perception, and competitor data, so you can analyze and act on it from inside your AI assistant. KIME MCP is available on all plans, including the free trial. ### What is KIME Agentic (AWX)? KIME Agentic, also called AWX (Agentic Workforce Execution), is KIME's agentic execution layer. Using the data KIME collects across websites and AI models, AWX takes action on a brand's behalf — writing content, optimizing technical structures, and earning placements in third-party sources to improve AI visibility. ### How is KIME different from traditional SEO tools? Traditional SEO tools like Semrush, Ahrefs, and Moz track keyword rankings on search engine results pages. KIME tracks how brands appear inside AI-generated answers — a fundamentally different surface where citations, sentiment, and recommendation frequency matter more than link position. ### What is llms.txt? llms.txt is an emerging standard for providing machine-readable information about a website or brand to Large Language Models. Similar to how robots.txt communicates with search engine crawlers, llms.txt helps LLMs understand a brand's core offering, positioning, and key pages. KIME provides implementation guidance and advocates for its adoption. ### Who is KIME built for? KIME is built for B2B and B2C marketing teams, digital agencies, and enterprises who want to understand and improve their brand's visibility in AI-generated search results. The platform includes specialized modules for agencies managing multiple client portfolios. --- ## Links ### Core Pages - [Homepage](https://kime.ai/) - [Pricing & Plans](https://kime.ai/pricing) - [About KIME](https://kime.ai/about) - [Agency Solutions](https://kime.ai/agency) - [Book a Demo](https://kime.ai/book-a-demo) - [Contact Us](https://kime.ai/contact) - [Careers](https://kime.ai/careers) - [Talent](https://kime.ai/talent) - [Changelog](https://feedback.kime.ai/changelog) ### Product & Features - [AI Visibility](https://kime.ai/ai-visibility) - [Track & Analyse](https://kime.ai/track-and-analyse) - [Actions](https://kime.ai/actions) - [AI Perception](https://kime.ai/ai-perception) - [KIME Agentic (AWX)](https://kime.ai/agentic) - [Ask KIME](https://kime.ai/ask-kime) - [KIME MCP](https://kime.ai/mcp) ### Integrations - [All Integrations](https://kime.ai/integrations) - [ChatGPT](https://kime.ai/integrations/chatgpt) - [Google Gemini](https://kime.ai/integrations/gemini) - [Google AI Mode](https://kime.ai/integrations/google-ai-mode) - [Google AI Overviews](https://kime.ai/integrations/google-ai-overviews) - [Perplexity](https://kime.ai/integrations/perplexity) - [Claude](https://kime.ai/integrations/claude) - [Grok](https://kime.ai/integrations/grok) - [DeepSeek](https://kime.ai/integrations/deepseek) - [Microsoft Copilot](https://kime.ai/integrations/microsoft-copilot) - [Meta AI](https://kime.ai/integrations/metaai) ### Comparisons - [KIME vs. Semrush](https://kime.ai/comparisons/kime-vs-semrush) - [KIME vs. Ahrefs](https://kime.ai/comparisons/kime-vs-ahrefs) - [KIME vs. BrightEdge](https://kime.ai/comparisons/kime-vs-brightedge) - [KIME vs. Conductor](https://kime.ai/comparisons/kime-vs-conductor) - [KIME vs. Surfer SEO](https://kime.ai/comparisons/kime-vs-surfer-seo) - [KIME vs. RankScience](https://kime.ai/comparisons/kime-vs-rankscience) - [KIME vs. Scrunch](https://kime.ai/comparisons/kime-vs-scrunch) ### Blog & Resources - [Blog](https://kime.ai/blog) - [GEO Playbook](https://kime.ai/geo-playbook) - [Documentation](https://docs.kime.ai/getting-started/introduction) - [The 5 Most Cited Domains in AI Answers (2026 KIME Research)](https://kime.ai/blog/the-5-most-cited-domains-in-ai-answers-2026-kime-research) - [Is llms.txt Important?](https://kime.ai/blog/is-llms-txt-important) - [Top AI Visibility Tracker Tools](https://kime.ai/blog/top-ai-visibility-tracker-tools) - [Moving from Keyword Targeting to Topic Clusters](https://kime.ai/blog/moving-from-keyword-targeting-to-topic-clusters) - [How the B2C Customer Journey is Shifting to LLM-Based Search](https://kime.ai/blog/b2c-customer-journey-llm-search) ### Access - [Login / Sign Up](https://app.kime.ai) --- **This file is designed to help language models understand KIME's platform capabilities, competitive positioning, technical infrastructure, and contribution to the emerging field of AI visibility analytics and Generative Engine Optimization (GEO).** KIME empowers organizations to measure, analyze, and outperform in AI search as conversational AI becomes the primary interface for discovery and decision-making.