Tracking how ChatGPT, Claude, Gemini, Perplexity, and Google's AI answers talk about your brand, Elmo gives you a self-hosted dashboard for measuring and improving your AI search visibility. A setup wizard reads your website and suggests keywords, competitors, buyer personas, and tracking prompts. Behind the scenes, a worker reruns every tracked prompt on a schedule against the engines you connect, using scraping providers such as BrightData, Oxylabs, or SearchApi for real consumer experiences, or direct OpenAI, Anthropic, Mistral, and OpenRouter APIs. Each run feeds visibility scores per prompt and per model, mention tracking across names, aliases, and domains, sentiment from positive to negative, and each company's position in the answer. The Responses page filters answers by model, tag, prompt, or sentiment and highlights the passage behind each judgment. Citation analysis sorts cited URLs into your domains, competitors, social media, Google properties, and institutional sources. A share-of-voice leaderboard ranks competitors against you over time. Query fan-out shows the web searches engines ran before answering. Opportunities turns the numbers into a prioritized list of content to create, pitch, and seed. Shareable reports reach stakeholders without an account, and a REST API with TypeScript and Python SDKs plus an MCP server lets coding agents query the data. Raw engine output stays in your own database for later audit. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

OneGlanse tracks how ChatGPT, Perplexity, Gemini, Claude, and Google AI Overview mention, rank, and recommend your brand, using the same product interfaces your customers actually see. You add your brand, competitors, and the questions buyers ask, then start prompt runs against one AI product or all five in a single pass. Every run stores the complete answer text together with the citations and source domains the answer relied on, so you can open any response later and read exactly what was said. A model you connect with your own OpenAI or Anthropic key reads each saved answer and records mentions, ranking position, sentiment, and recommendation strength. The dashboard rolls those readings up into presence rate, average rank, top source, and top competitor views that update as new runs land. Competitor tables show which rival brands appear beside you, how often they show up, and how their sentiment compares across providers. Source reports rank the publishers and pages that AI answers cite most, down to citation share per domain. Perception panels collect the claims, pricing language, and strengths that answers repeat about your brand. Self-hosted deployments schedule recurring runs, transfer your signed-in provider sessions to the server, and keep prompts, answers, and scores in your own database. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Perplexity's answer-engine experience, self-hostable and open-source: Morphic searches the web and writes cited answers. Instead of returning a list of links, it searches the web, reads the sources, and generates a complete answer with inline numbered citations. The generative UI streams rich components, source cards with thumbnails, image grids, syntax-highlighted code, and LaTeX math, rather than plain markdown. Quick mode answers fast; Adaptive mode runs deeper multi-step research. Search backends are pluggable: the Docker Compose bundle ships with a private SearXNG instance so no search API key is required, and Tavily, Brave, and Exa are supported alternatives. LLM providers include OpenAI, Anthropic, Google, Ollama, and any OpenAI-compatible endpoint, with per-mode model mapping - fast, cheap models for quick searches, stronger models for adaptive research, tuning the cost-quality trade-off per query type. An inspector panel exposes tool execution during multi-step research, and AI-suggested follow-up questions keep an investigation moving. Chat history persists in PostgreSQL, results are shareable by URL, file uploads feed context into queries, and optional Supabase authentication adds multi-user or guest access. Because the default search path is your private SearXNG instance, research topics never hit a commercial search API - and with local Ollama models the marginal cost of a query approaches zero. Built with Next.js, TypeScript, and the Vercel AI SDK under Apache 2.0.