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ClarityQ Debuts with $3.7M to Automate Digital Product Usage Analysis

ClarityQ Debuts with $3.7M to Automate Digital Product Usage Analysis

By Lucy Unicorn 03 March 2025
Three people in black t-shirts with "ClarityQ" logo smile while sitting on a bench in a green park setting.

ClarityQ Co-Founders (L-R): Ronnie Sternberg (CBO), Orly Shoavi (CEO), and Adi Ashkenazi (CTO)

Israeli startup ClarityQ Inc. launched on Friday (Feb 27) with $3.7 million in pre-seed funding and plans to apply artificial intelligence to the often complex process of answering questions about technology product usage.

Founded by a trio of entrepreneurs with a track record of previous startups and exits, the company employs technology that uses generative and agentic AI technology to present answers to product-related questions through a conversational dialogue. It’s aimed at product managers, data analysts and managers in software-as-a-service web, mobile app and gaming companies.

Digital usage analysis encompasses data on how users interact with a product, allowing for quick adjustments and iterative improvements. Insights based on detailed user actions such as clicks, session duration and feature adoption help product teams identify patterns and friction points that aren’t easily captured by surveys or direct feedback. Understanding engagement helps optimize programs such as free trials, improving conversion rates and increasing user retention.

ClarityQ is primarily focused on business-to-consumer scenarios such as mobile and SaaS applications that can involve millions of users and very large data sets. The platform automatically generates SQL queries and delivers detailed, validated answers, including tables, charts and visualizations.

Co-founders Ronnie Sternberg and Orly Shoavi (pictured, left and center) previously started SafeDK Mobile Ltd., a software development kit management tool for mobile app developers, and sold it to AppLovin Corp. in 2019. Co-founder and Chief Technology Officer Adi Ashkenazi (right) founded Octarine Inc., a security platform for protecting software containers, and sold it to VMware Inc. in 2020.

Multi-agent architecture

ClarityQ converts text to SQL techniques to access raw and summarized data and integrates a multi-agent validation engine to minimize errors and ensure reliability. Each answer is accompanied by a confidence score and can include charts and other images.

ClarityQ works with customers’ existing data warehouse platforms, including the Snowflake Inc. Data Cloud, Google LLC’s BigQuery, Amazon Web Services Inc.’s RedShift and the open-source Postgres database management system. Installation and configuration typically requires about two weeks of training.

“Training is extensive,” Shoavi said. “We have a thorough understanding of process of the customer’s data. Events vary from product to product and there are hundreds of parameters for each data point.”

Once a model is trained, users can ask questions in natural language. Agents validate SQL queries to ensure that answers are consistent and valid. Users are presented with a set of predefined questions and can formulate their own.

The software also automatically generates a table catalog and detailed information about parameters. That feature was originally a “marketing hack” that turned out to have value for customers, Shoavi said.

“Most companies don’t have an automated system for event management,” she said. “They put the data in an outdated Excel file or messy Google sheet and it’s messy. We want to make everything as automated and fast as possible.”

Funding was led by Tel Aviv-based State of Mind Ventures with angel investors.

Source: SiliconANGLE

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ClarityQ

ClarityQ

ClarityQ addresses the challenge faced by product decision-makers in SaaS or app companies, who often struggle to analyze complex data while analytics teams are too busy to assist.

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