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ai-analytics

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posthog

🦔 PostHog is an all-in-one developer platform for building successful products. We offer product analytics, web analytics, session replay, error tracking, feature flags, experimentation, surveys, data warehouse, a CDP, and an AI product assistant to help debug your code, ship features faster, and keep all your usage and customer data in one stack.

  • Updated Mar 22, 2026
  • Python

API-first semantic engine and query planner for AI agents that compiles declarative YAML models into optimized, dialect-specific SQL across BigQuery, PostgreSQL, Snowflake, ClickHouse, Dremio, Databricks, and DuckDB.

  • Updated Mar 22, 2026
  • Python

A complete machine-learning system that predicts AI assistant user satisfaction using behavioral signals such as device, usage category, time features, session metrics, and model metadata. Includes full ML pipeline, SHAP explainability, evaluation suite, and an interactive Streamlit analytics dashboard.

  • Updated Dec 5, 2025
  • Python

Open-source agentic schema for reliable data outputs. Query data through MCP and via our SDK. Create apps, embed data or just simply explore through your preferred agent.

  • Updated Mar 3, 2026
  • TypeScript

Ontology-based MCP server that analyzes database schemas (PostgreSQL, Snowflake, ClickHouse, Dremio) and generates RDF/OWL ontologies with SQL mappings for fan-trap-free Text-to-SQL.

  • Updated Mar 22, 2026
  • Python

Full-Funnel AI Marketing Analytics. A modern data stack powered by dbt MetricFlow and MCP. Natural language insights across Google/Meta Ads, CRM, and 5 data warehouses. Includes XGBoost lead scoring and a $0/mo architecture.

  • Updated Mar 16, 2026
  • Python

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