Querri Overview: Querri is an AI-powered data analytics platform designed to help business teams work with real-world data from start to finish. It supports the full analytics lifecycle—from connecting and preparing raw data to analysis, visualization, and dashboards—using natural language rather than SQL or custom code. Unlike tools that focus primarily on chat-based analysis or static reporting, Querri is built as an end-to-end system for analyzing data across multiple sources in a structured, repeatable way. It is intended for teams that need reliable insights from operational, financial, or customer data without relying on dedicated data engineering resources. Data ownership, privacy, and compliance: Querri is designed with data governance and security as core requirements. The platform is SOC 2 Type II compliant, and customer data is not used to train AI models. Data remains owned and controlled by the customer, with clear access and security controls. This makes Querri suitable for teams working with sensitive or regulated data, including finance, operations, and customer analytics, where consumer-grade AI tools may not meet compliance or trust requirements. End-to-end analytics in one platform: Querri brings multiple analytics capabilities into a single environment: - Connect spreadsheets, cloud storage, and databases - Profile, clean, and standardize messy data with AI assistance - Join multiple datasets to create analysis-ready views - Analyze trends, segments, and drivers - Generate charts, tables, and dashboards By combining preparation, analysis, and reporting in one system, Querri reduces the need to move data between separate tools or rebuild work at each step. AI designed to act like a data analyst: Rather than functioning as a generic chat interface, Querri’s AI is designed to behave more like a data analyst. It understands dataset structure, suggests relevant next steps, and provides guided prompts based on the data available. Clickable suggestions help users get started and explore their data without needing to know what to ask upfront, which is especially useful for non-technical users or teams new to analytics. Multi-source analysis: Querri supports analysis across multiple data sources at once. Users can maintain a shared data library and ask questions across all connected datasets from a single interface. The AI identifies relevant sources and handles joins and alignment automatically. For more complex use cases, users can explicitly combine datasets into projects to analyze relationships across systems, such as connecting marketing, sales, and financial data. Repeatability and Automation: For every question or analysis, Querri automatically generates and saves the underlying Python code. This allows analyses to be reused, refreshed, and automated over time rather than treated as one-off outputs. Dashboards and workflows can be updated with new data on a schedule, supporting both exploratory analysis and ongoing reporting without rebuilding logic. Transparency and explainability: Querri emphasizes transparency in how results are produced. Users can: - View step-by-step explanations of each analysis - Inspect the generated code behind results - See which methods or calculations were applied - Switch between conversational and structured data views This approach helps users understand and trust results, which is especially important for decision-making in finance, operations, and leadership contexts. Dashboards and downstream use: Querri includes a dashboard builder that stays connected to the underlying data and analysis. Charts and tables are interactive, can be downloaded, and can be added directly to dashboards. Users can move from a dashboard back into the data to ask follow-up questions, making dashboards an entry point for exploration rather than a static endpoint. Ideal users and use cases: Querri is well-suited for: - Business, finance, operations, and marketing teams - Organizations without large data engineering teams - Teams analyzing data across multiple systems - Users who value transparency, governance, and repeatability For teams that need an AI-powered analytics platform capable of handling real data complexity—from ingestion through dashboards—Querri provides a structured alternative to chat-only or visualization-only tools.