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ClarityQ is an AI-powered data analytics platform that lets anyone in your organization ask questions about your data in plain English and get accurate answers, insights, and visualizations — no SQL or data expertise required. ClarityQ connects to your data warehouse and builds a Context Layer — a rich semantic model of your business data. Our AI agent actively helps build this layer, leveraging your existing documentation, semantic definitions, and data structure to accelerate the process. Once context is in place, your data team stays focused on high-impact work while product, marketing, operations, and business teams get the answers they need — instantly and independently.

How It Works

ClarityQ works in two phases: building context and asking questions.
1

Connect Your Data Warehouse

Connect ClarityQ to your data warehouse — BigQuery, Snowflake, Redshift, PostgreSQL, Databricks, or MaxCompute. ClarityQ uses read-only access to query your data securely.
2

Build Your Context Layer

ClarityQ learns your business by building a Context Layer — a semantic model that maps your raw data to business concepts like metrics, features, segments, and dimensions. This is what makes ClarityQ’s answers accurate and relevant to your organization.
3

Ask Anything

Once context is built, anyone on your team can ask data questions in plain English. ClarityQ’s AI agent translates questions into SQL, executes queries, and returns answers with charts, tables, and insights.
4

Automate and Scale

Schedule recurring questions as automated tasks, share conversations with your team, and build up memory so ClarityQ gets smarter over time.

Key Capabilities

Ask Anything

Ask data questions in natural language. ClarityQ generates SQL, runs queries, and returns answers with rich visualizations — no SQL or data expertise required.

Context Layer

A searchable semantic layer that maps your raw data to business concepts. Includes table catalog, event catalog, semantic catalog, memory, and skills.

Automations

Schedule recurring questions as tasks and receive answers automatically via email or Slack on a cadence you define.

Memory

A two-tier memory system (personal and product) that retains context across conversations and improves answers over time.

Semantic Catalog

Define metrics, features, segments, and dimensions that reflect how your business thinks about data — not how your database stores it.

Skills

Encode your team’s best analysis methodologies into reusable skills. The AI agent follows them step by step — asking clarifying questions, executing the analysis, and validating results — so complex workflows run consistently every time.

Who Is ClarityQ For?

RoleHow ClarityQ Helps
Data AnalystsBuild and maintain the context layer, embed ClarityQ into daily workflows, and run sophisticated analyses in minutes instead of hours or days.
Product ManagersGet instant answers about user behavior, feature adoption, and funnel metrics without waiting for the data team.
Marketing TeamsAnalyze campaign performance, cohort behavior, and conversion rates in natural language.
Business & OperationsTrack KPIs, monitor trends, and generate reports on demand.
Data EngineersMaintain the context layer and keep business definitions aligned with the underlying data.