GEOInflow is a self-hosted analytics platform that shows website owners which AI crawlers visit their pages, what those crawlers read, and how much traffic and revenue AI search actually sends back. Import a sitemap, CSV, or JSON inventory and the coverage report compares it against observed crawl logs, flagging important pages that no AI crawler has ever requested and directories where coverage keeps dropping. The built-in catalog recognizes 61 AI crawler identities, including crawlers from OpenAI, Anthropic, Perplexity, Google, Microsoft, ByteDance, Baidu, Kimi, and Tencent Hunyuan, and separates training, AI search, and user-triggered visits. Verification combines declared user agents with official IP ranges and DNS evidence, so a spoofed crawler name never counts as a confirmed visit. Browser tracking connects AI search referrals to landing pages, custom events, goals, funnels, and conversions, letting teams measure whether visibility in AI answers turns into signups and sales. Alongside the GEO reports, teams get pageviews, unique visitors, referrers, geography, devices, heatmaps, retention, and visitor paths, with CSV, JSON, and ZIP exports for any selected scope. Workspaces, team permissions, and public sharing links let agencies and publishers give each client or department its own dashboards without exposing raw data or other sites. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

With 5,600+ GitHub stars and deep dbt integration, Lightdash is the open-source Agentic BI platform that treats analytics like software — defining metrics, dimensions, joins, permissions, and caching in a governed context layer that powers dashboards, AI agents, data apps, embedded analytics, and MCP server endpoints simultaneously. The dbt Write-Back feature lets business users create custom metrics and models in the UI, then automatically generates pull requests in GitHub or GitLab so every change flows through code review and CI validation before reaching production. Context-specific AI analysts automatically select relevant models and metrics, build queries, and present insights in plain English, while row-level security, user attributes, and customer-facing permissions ensure data governance at every layer. The platform connects to BigQuery, Snowflake, Redshift, Databricks, PostgreSQL, Trino, and ClickHouse through warehouse adapters, with the TypeScript monorepo built on React, Mantine, Vite, and TanStack Query on the frontend plus Node.js, Express, Knex, and PostgreSQL on the backend. Data teams build analytics with coding agents, preview changes from the CLI, validate in CI pipelines, and review charts and dashboards in pull requests — making the entire analytics lifecycle version-controlled and reproducible. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.