CUBOT BI enhanced with Sentissa AI: Defensible, context-specific and secure on-premise AI

Learn more about Sentissa

Conversational Intelligence from Data

Get answers from your data via chat interfaces

  1. Conversational chat interface uses a metric agent

  2. Retrieval Augmented Generation (RAG) for context-specific answers to organizational data and questions

  3. CUBOT BI Semantic Metadata layer for improved query responses

  4. Narrative results summary

Three-Tiers of Offerings

Metric Agent

Fetches Answers from Conversational Queries - understands context and builds on CUBOT BI's semantic layer which has been part of the original architecture

Insight Agent

Reasons over data using Sentissa's graph-based deterministic causal AI. Users ask questions in natural language and get reasons and causation for changes observed in data. Root causes are easily visible to users.
Sentissa AI provides appropriate recommendations to results from the metric and insight agents, in order for business teams to take action. Coming soon in 2027.

Decision Agent

Causal Reasoning, On-Premise, Deterministic AI via Sentissa AI Integration

  • Causal AI that uses deterministic, graph grounded logic where answers are traceable and defensible

  • On premise LLM / SLM Libraries

  • Optimized performance with CUBOT semantic layer

  • Can build further onto data in your Data Warehouses

  • Integration with CUBOT BI Platform for more options on reporting, dashboards, charts, dissemination of information, CUBOT security matrix

See a sample 3-tier offering for BFSI