ClarityQ
Overview
Agentic data analytics platform that tells you what to do next.
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ClarityQ is an agentic data analytics platform for data, product and business teams. You connect your warehouse (Snowflake, BigQuery, Redshift, Databricks, Postgres, Athena, Azure Synapse and more), ask questions in plain language, and get deep analysis, visualizations, insights and action plans - no data remodeling required.
At the core is a Context Layer that stays current on its own: business logic, metric definitions and table relationships are built and maintained automatically, with every change tracked and reviewable. Every answer shows its reasoning, the SQL it ran and the sources it used, and a built-in validation engine checks the results. When a question is ambiguous, ClarityQ asks instead of guessing.
You can combine multiple data sources in one query, generate dashboards from a prompt, and schedule automated reports to Slack or email. Sharing is role-aware and governed, and there's an open API. Security is read-only by default, with SOC 2 Type II, GDPR, Private Link and a single-tenant option.
ClarityQ is used by gaming, SaaS, e-commerce and consumer app companies including CrazyLabs, Softonic, Spiral Interactive, AppGeneration and Zaffic. Pricing is pay-as-you-go.
Product overview
Capabilities, pricing and fit
ClarityQ is positioned as an agentic analytics product that combines natural-language data analysis with a continuously maintained context layer, dashboard generation and automated reporting for teams working with complex business data.
Information as of October 19, 2026
What it can do
- Natural-language analytics
Users can ask questions in plain English and receive data, visualizations, insights and action plans in one response.[1]
- Auto-maintained context layer
ClarityQ says it builds and maintains context, semantic layers and data catalogs covering business logic, metrics, rules, table connections and in-app events.[1]
- Cross-source analysis
The platform is described as cross-source by design, allowing one question to combine data from areas such as sales, finance, revenue, marketing spend and product.[1]
- Interactive ambiguity handling
When questions involve ambiguity such as duplicate metrics, overlapping definitions or missing periods, ClarityQ surfaces choices instead of silently guessing.[1]
- Transparent reasoning and validation
The official page lists transparent reasoning, SQL and sources behind every answer, along with a built-in validation engine.[1]
- Prompt-created dashboards
ClarityQ can generate full dashboards from a single prompt and lets users edit and query dashboards in natural language.[1]
- Automated reporting
The product page describes automated reports delivered to mailbox or Slack.[1]
- Governed collaboration
The page describes governed, collaborative and role-aware access for sharing analytics and dashboards across teams.[1]
Where it fits best
- Data, product and business teams that want to ask natural-language questions and receive answers, visualizations, insights, action plans, dashboards and reports.[1]
- Teams working across multiple data sources, because the product page describes cross-source analysis that can combine areas such as sales, finance, revenue, marketing spend and product data in one ask.[1]
- Game, digital, e-commerce and SaaS teams, which are specifically named in the official page description and navigation context.[1]
Important considerations
- The supplied official page context does not show public plan prices, a starting price, billing period, free plan or free-trial terms.[1]
- The product depends on connected business data and maintained context; the page describes less than two days from connection to first trusted answer and mentions human-in-the-loop validation when necessary.[1]
- Independent community or review evidence was not supplied; adoption evidence in the available context is limited to the official page’s customer testimonials and vendor-reported metrics.[1]
Sources (1)
- ClarityQ Agentic AI Data AnalysisOfficial site · checked 2026-10-19
Autonomy level
68/100
Our subjective rating of how independently the product carries out its documented tasks, considering the human setup, input, approval and review it needs. This is not a measured success rate.
Comparisons
Custom Comparisons
Some of the use cases of ClarityQ:
- Asking plain-language questions across business data
- Generating dashboards from prompts
- Producing recurring analytics reports
- Analyzing product, marketing, finance and game data together
- Maintaining shared business context for analytics teams
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Popularity level: 36%
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