ClarityQ Data Catalogs: One Source of Truth for Your Data

ClarityQ has been a real game-changer for us! It lets our entire gaming team work with data at scale. We’re querying billions of events and dozens of tables, with in-depth analysis delivered in seconds. It empowers both analysts and game owners with 5× greater efficiency and real data superpowers - saving countless hours of analysis and enabling faster, better decisions.

Guy Tomer

Co-founder & COO, CrazyLabs

ClarityQ became a critical decision layer for us, turning complex behavioral data into clear actions. We identified friction points in our onboarding and loyalty mechanics, which led us to remove low-impact features and focus on real revenue growth.
‍

Avner Azulay

Director of Product, Zaffic

ClarityQ lets our Marketing and Product teams get answers in minutes instead of hours. We used to juggle Firebase, GA, AdMob, Adjust - now everything lives in one place. Our analysis is easily 10x faster, saving us hours every time. But the real game-changer is the insights we wouldn't have found on our own - things we didn't even know to look for.

Eduardo Carqueja

CEO, Appgeneration

ClarityQ (or "Clara" as we refer to it) functions as a co-pilot analyst providing me and other stakeholders (including users who are resistant to use the standard reporting tools available in the company) with business insights via very friendly and convenient interface and visual outputs.

Mark Shohat

Head of Business Analysis, Spiral Interactive

Thanks to the ClarityQ Agent and strong team support, we found the perfect analysis wingman. It has significantly sped up our deep-dive analyses, is expected to cut analysis time by at least half and has freed up time to focus more on strategic work.
‍

Marcos del Molino

Data Analyst, Softonic

The Contextual Logic Engine - Your Enterprise’s Brain

Consistent

But Flexible

Governed

But Transparent

Dynamic

But Unified

Integrated

But Autonomous

Autonomous Context Layering - in 3 Steps:

Ingestion

"Builder" agents map every table, column, and event in your warehouse - plus the metrics already defined in your BI tools and the queries your team actually runs. The layer starts grounded in your real data and your team's real usage, not a generic schema.

Pattern intelligence

From that map, the agents propose business-ready definitions - entities, dimensions, and the exact SQL behind metrics like Gross Margin or Active Pipeline. The same number means the same thing in every dashboard, report, and answer.

Data Resilience:

As your warehouse evolves, agents continuously reconcile the layer with reality - handling schema drift, duplicates, and gaps on their own. When a change is ambiguous, the agent asks you to clarify rather than guess, so definitions never silently drift

All-in Dynamic and Autonomous Semantics

BI Layer Sync

Auto ingestion of metrics from Tableau, Looker or alike

Dynamic & Live

Continuous, live crawling tracks event types, table schemas, metadata, and "ACTIVE" statuses in real-time.

Flexible Editing

Edit descriptions, SQL logic, and entity mappings at any time.

Data Change Alerts

Automatic email notifications when new columns, events, or parameters are detected.

Open API & Ecosystem Sync

Use the API to sync your existing semantic layer and enrich the Context Layer.

Version and Approvals Control

Track every change in metrics or logic, and ensure robust approval workflows.

On-the-Fly Expansion

Add new metrics, segments, or entities directly from the chat.

Skills

Reusable, pre-approved analytical templates that ensure that the answers use consistent methods every time.

Memory

ClarityQ remembers your instructions and preferences across conversations, getting more personal and accurate with every interaction.

Continuous Version Control

Every change to a definition is treated the way an engineering team treats a pull request: tested in isolation, reviewed, audited, and versioned. Not once at setup - every time.

Step 1

Creation

The agent drafts the metric and the SQL, and asks where the request is ambiguous.

Step 2

Private soft launch

Private and unpublished. Only the requester can query it and test it against numbers they trust.

Step 3

Review

Visible to reviewers. A data owner checks the logic, not the requester.

Step 4

Audit

Does it duplicate, conflict, or change the meaning of a query that already runs?

Step 5

Deploy

Published to the workspace with a version number and a changelog entry.

The layer proposes its own changes, and every proposal goes through the same five steps before anyone else sees a different number.

Learns From Every Question

The Context Layer improves from real usage, not from manual upkeep. Every correction, gap and edit becomes a proposal - and every proposal goes through the same five steps before it ships.

A correction in a session

A user tells the agent "no, exclude wholesale." The correction is captured and queued for review, instead of dying in one conversation.

A gap the agent spots

ARPPU asked 12 times, never defined. The agent flags what it improvised, ranked by how often it came up, so the biggest gaps get fixed first.

An analyst's edit

An analyst changes a definition directly in the Builder. It still gets tested, reviewed and audited like any other change.

Why this works: the same agent that maintains the context also answers the questions. It sees every question, every thumbs-down and every correction - and that usage is what feeds the fixes.

Automated Data Structuring & Governance

How it works

ClarityQ autonomously scans your warehouse and classifies every table into six categories (Raw Data, Dimension, Fact, Aggregate, Lookup, or Events) with auto-generated descriptions down to the column level.

What you get

Table type distribution, column-level metadata completeness, and approval coverage across your entire warehouse.

Why it matters

Every table and column is documented, classified, and governed, with column-level approval workflows so your AI agent only uses what your team has reviewed.

Real-Time Activity Mapping

Cross-Platform Event Intelligence

How it works

Automatically discovers and catalogs every event across your product (Custom and Automatic), with full parameter breakdowns, AI-generated descriptions, and dedicated views for Common Parameters and User Properties.

What you get

Event recency and volume across platforms and versions, parameter-level approval coverage, and description completeness, filterable by platform, version, and status.

Why it matters

Deepens the analysis by linking between different operations, such as user engagement to revenues, or sales to marketing.

Governed Business Intelligence

How it works

Centralizes your metrics, segments, features, and entities into a managed knowledge base. Complex calculations (session_duration, iap_revenue, ecpm) live alongside the core entities (Customers, Assets) and their unique attributes, all mapped and approved by your team.

What you get

Aggregated performance indicators, user segments, and a complete map of the entities and attributes that define your business.

Why it matters

When everyone queries through ClarityQ, they get the same definitions, the same math, every time. No conflicting numbers across teams, no hallucinations. Your business knowledge becomes a shared, trusted asset.

Persistent Intelligence Across Every Conversation

How it works

ClarityQ remembers instructions, preferences, and context across all your chats. Just say "Remember that xyz..." and it sticks. Product Memory is added to enhance product-wide shared knowledge.

What you get

An agent that deeply knows your style and preferences, much like a senior team member.

Why it matters

Efficiency is enhanced when the team knows how to collaborate on multiple projects without needing to calibrate every single time. An agent that can’t maintain a similar path becomes a burden.

Pre-Built Analytical Workflows

How it works

Define your analytical workflows once - like root cause analysis frameworks, version release playbooks, or cohort deep-dives - and save them as reusable Skills. When you need them, just trigger the Skill and ClarityQ runs the full analysis for you..

What you get

Your best analytical thinking, captured and repeatable. No more rebuilding the same logic from scratch, no more forgetting a step mid-analysis.

Why it matters

Great analysis shouldn't require starting from scratch every time. Skills let you run your most important workflows on demand and receive consistent results, no matter who's asking and when.

Frequently Asked Questions

View all

Build the Strongest Context Layer Possible. Then Keep It That Way.

Uncompromised Accuracy Starts Here.