Kubit, the customer journey analytics platform known for its warehouse-native architecture, has introduced Ask Kubit, a conversational AI interface that turns plain-English questions into on-demand analytics.
Built on the company’s Kubit Lumos engine, Ask Kubit aims to eliminate bottlenecks in data access by delivering explainable AI (xAI) insights directly from governed warehouse data—without coding or dashboard-building.
From Question to Answer in Seconds
With Ask Kubit, users simply type a question like, “What was our conversion rate last quarter for new mobile signups?” The AI interprets intent, generates a query, and returns a complete, contextual report in seconds.
Key capabilities include:
- Natural Language Querying: Everyday language in, complete answers out—plus context on how results were calculated.
- Smart Suggestions: AI-driven follow-up questions keep the analysis flowing without switching tools.
- Source-of-Truth Metrics: Reports are grounded in governed, warehouse-native data for maximum transparency.
- Lumos Integration: Extends Lumos’s NLP and summarization into a conversational analytics workflow.
Explainable AI, Not a Black Box
CEO Alex Li says the goal is simple: “Analytics should be as easy as asking a question.” Kubit claims Ask Kubit reduces AI hallucinations by using secure metadata already connected to the platform, while VP of Product Jeremy Benza stresses the transparency: “Because Ask Kubit runs directly on your cloud data warehouse, there’s no hidden logic. Every answer is traceable and based on reliable data.”
Targeting Enterprise Analytics Bottlenecks
Ask Kubit is available now for Enterprise customers. Kubit is positioning the tool as a way to:
- Accelerate product and business decision-making.
- Reduce dependence on overburdened analytics teams.
- Keep sensitive data under customer control.
By combining conversational AI with a warehouse-native model, Kubit hopes to replace static dashboards with dynamic, trustworthy dialogue—turning every business user into a self-service analyst.
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