Querio is an AI-native BI platform built to remove the bottleneck between business questions and reliable data answers. Instead of waiting on tickets or wrestling with traditional dashboard tools, users ask questions in plain English and get instant, explainable insights; with the option to drill down, refine filters, or edit the underlying SQL/Python at any time. Under the hood, Querio connects directly to modern data warehouses and databases (such as Snowflake, BigQuery, and Postgres) so every query runs on live, governed data — no extra data duplication or proprietary storage. A context layer lets data teams define joins, metrics, and business terminology once, and Querio’s AI agents reuse that knowledge for every query, keeping answers consistent across the organization. For business users, Querio feels like a conversational analyst: ask a question, follow up with “break this down by region” or “show last year instead,” and watch the visuals update while context is preserved. For technical teams, it’s a fully transparent workspace where generated SQL and Python are visible, editable, and versioned; ideal for deeper analysis and validation. querio.ai. Querio also powers embedded analytics experiences, letting product and platform teams ship AI-driven reporting directly inside their own applications. Theme tokens and APIs help match your design system so customer-facing analytics look and feel native. querio.ai Security and governance are first-class: Querio is SOC 2 Type II audited, uses read-only database connections with encrypted credentials, offers granular access control, and never uses your data or queries to train external models. Key Features Natural language querying & conversational analytics: Ask questions in everyday language, refine with follow-ups, and drill into details without writing SQL — the AI agent handles translation and context. Agentic notebooks (coding optional): Work in agentic notebooks where prompts, generated SQL/Python, charts, and narrative outputs live together. Business users stay in prompt mode; technical users can drop into code for fine-tuning. Explore - instant insights on live data: The Explore workspace lets you start from a prompt, iterate freely, drill down as many times as you need, and adjust filters or visualizations on the fly. AI-assisted dashboards & boards: Automatically generate charts and tables from questions, then organize them into dashboards and boards to track KPIs or tell data stories that stay synced with live data. Embedded analytics & AI experiences: Deliver customer-facing analytics that “just works”: embed AI-powered questions, charts, and tables into your product with APIs and theming tokens to match your design system. Context layer & business metrics: Define table relationships, business metrics, and glossary terms once; Querio’s AI then uses this context to keep answers consistent and trustworthy across all teams. Tagging, schema awareness, and data transparency: Tag unique database values inside prompts, quickly see what data Querio can access, and inspect the code it wrote; no hidden logic or “black box” queries. Stop & edit, full control for power users: Pause a run, tweak filters or generated SQL/Python, and re-run without leaving the workflow. This gives analysts the control they expect with the speed of AI. Version control for outputs: Update analyses and dashboards while keeping previous versions safe, so teams can compare past and present results without losing work. Secure, governed access: SOC 2 Type II, read-only access to databases, granular access control, and a policy that no LLM usage is ever used for training — even on the enterprise plan. *Typical Use Cases* For Product & Growth teams: - Funnel, activation, and feature adoption analysis - Experiment and cohort analysis without writing SQL - Self-serve product analytics embedded directly into the app For Revenue, Sales & Marketing: - Pipeline, MRR/ARR, and retention reporting - Campaign performance and attribution analysis - Shared boards for weekly and monthly business reviews - Operations & Support - Monitoring operational KPIs and SLAs in real time - Identifying bottlenecks and anomalies with follow-up questions - Answering ad-hoc performance questions without Excel exports For Data & Analytics teams: - Centralizing metrics, joins, and terminology in a single context layer - Reducing the data-request backlog while retaining governance - Reviewing and hardening AI-generated SQL/Python in a transparent workspace querio.ai - Embedded analytics for SaaS products (Adding self-service analytics to customer portals)