SCIKIQ approaches conversational analytics differently from traditional BI tools and generic GenAI chat interfaces. Instead of placing a chat layer on top of dashboards, SCIKIQ embeds conversational intelligence directly into its semantic data platform.
At the core of SCIKIQ’s conversational analytics is a unified semantic layer built using both technical metadata and business metadata. Technical metadata captures how data is stored, transformed, and connected across systems, while business metadata defines KPIs, metrics, hierarchies, and business rules in language that business teams understand. By combining the two, SCIKIQ creates accurate, governed definitions that serve as the foundation for every conversation.
Conversational Analytics Grounded in Data Semantics
When users ask questions in SCIKIQ, the platform does not rely on pattern matching or keyword translation alone. It uses semantic understanding to interpret intent, resolve ambiguity, and map the question to the correct business definitions. This ensures that questions like “revenue,” “growth,” or “churn” are always interpreted consistently across teams and use cases.
This semantic grounding is what allows SCIKIQ to deliver reliable conversational analytics at enterprise scale, even in complex, multi-source data environments.
KPI Deep Dive Through Conversation
SCIKIQ’s conversational analytics is tightly integrated with its KPI Deep Dive Engine. KPIs in SCIKIQ are modelled as semantic entities with clear definitions, dependencies, and lineage. This allows users not only to ask what a KPI value is, but also why it changed.
Through simple follow-up questions, users can automatically drill into contributing dimensions, identify anomalies, and understand root causes, all without predefined dashboards or manual analysis. Conversational analytics becomes a natural entry point into deeper KPI intelligence.
Also read: What is conversational analytics and how does it work
GenAI and LLMs – Used Responsibly
SCIKIQ leverages GenAI and large language models to enhance natural language understanding and reasoning, but all responses are constrained by governed semantics, metadata, and access controls. This prevents hallucinations and ensures every answer is traceable back to trusted data.
Unlike generic AI tools that generate insights freely, SCIKIQ ensures conversational analytics remains accurate, explainable, and audit-ready.
Designed for Business Teams, Trusted by Data Team
For business users, SCIKIQ delivers a simple conversational experience, ask questions and get answers. For data and IT teams, it provides control, consistency, and governance through metadata-driven semantics.
This balance allows organizations to scale analytics adoption without compromising trust, security, or data integrity.
From Conversations to Decisions
By combining data semantics, conversational analytics, and KPI deep dive capabilities into a single platform, SCIKIQ transforms how enterprises interact with data. Conversations turn into insights, insights into understanding, and understanding into confident decisions.
SCIKIQ doesn’t just help users talk to their data it helps data talk back with meaning.
