"What made revenues spike last week?"
ClarityQ answers open-ended questions across any data, like where product meets finance, without compromising context or accuracy. It catalogs billions of tables, metrics, and events into a unified contextual layer in days, then delivers answers with visuals, insights, and a clear action plan.
Go from messy tables to meaningful discovery in just days. Ask any question, drill into any metric, and pivot between dimensions to generate in-depth analyses and build a comprehensive understanding of root causes. Turn a single conversation into a validated set of insights that your team can align and act on, fast.
ClarityQ’s agent is built for complex analytics, autonomously managing the entire journey: planning, reasoning, and validating every answer to ensure every insight and visualization is reliable and grounded in your specific data.
ClarityQ automatically structures your data semantics, updates them, and flags gaps - building on your existing BI definitions and business logic. It applies guardrails to ensure every answer is grounded in your specific context, and stops for clarification when needed rather than hallucinating or guessing - delivering transparent, well-grounded results you can trust, always.

Schedule any question to run on its own - daily, weekly, or monthly. Set it once, and ClarityQ delivers fresh results automatically via email, Slack, or the dedicated Results tab. Create an automated task straight from the chat or from the Automations tab, so insights keep flowing even when you're not in the room.
Context-Driven data streamlining & mapping
Our proprietary GenAI-based tech performs entity resolution, context mapping, and schema change analysis to create a comprehensive Event Catalog enriched with useful, automatically-created metadata.
Company-specific AI model
Using company-specific customizations to the model, including example-based learning, schema linking, and automatic dataset creation ensures an enhanced, tailor-made model performance.
Accuracy as a key to success
For robust quality assurance of its accuracy, ClarityQ employs a range of advanced, academically-supported mechanisms for ensuring the accuracy of its outputs, incorporating various verification and validation techniques as well as ensemble methods for quality assurance.
Connect your data
Use a secure, guided wizard to connect ClarityQ to your data warehouse using a service account or your preferred auth method, and optionally connect BI tools and semantic layers
Read-only access to your warehouse
Additional integrations are optional and help enrich definitions and accelerate Context Layer readiness
Review and approve your Context Layer
ClarityQ generates business definitions, metrics, and contextual catalogs - you review, adjust, and approve what becomes your source of truth.
Start using ClarityQ
Start asking questions and get answers - make data-driven decisions faster than ever.
Answers without the queue. Product, growth and business teams ask in plain English and get charts, funnels and retention curves from live warehouse data - no SQL to write, no dashboard to request, no waiting on an analyst.
Analysts move faster. ClarityQ works as a co-pilot for the data team, automating routine SQL and repetitive queries so analysts spend their time on the work that actually needs judgement.
Your data stays where it is. ClarityQ connects to your warehouse with read-only access and never copies or stores your data, so your existing permissions and governance continue to apply.
ClarityQ resolves ambiguity rather than guessing at it. It uses your Context Layer - the table, event and semantic catalogs - to map loose phrasing onto the right tables, metrics and segments, then shows the generated SQL alongside a plain-English explanation of how it read your question.
If a question is genuinely open to more than one interpretation, you can see exactly which one ClarityQ took and refine from there, rather than being handed a number with no way to check it.
Yes. ClarityQ surfaces relevant follow-up questions as you explore, drawn from your Context Layer and from the answer you just received. When a result raises an obvious next question - a segment behaving differently, a drop that needs a cause - ClarityQ offers it, so you can keep going without knowing your schema or guessing what is worth asking next.