Upload every request, ticket and review you have. Find which product problems are actually costing you customers, and which are just loud.
Counting requests rewards whoever complains most. On a ranked list, 400 trial users and 9 of your largest accounts look the same.
Unified Data & Enrichment
Start with one file of tickets, reviews or verbatims. Every record comes back enriched with structured Dimensions: product area, feature mention, root cause, severity, churn risk. Not a summary of the pile. A typed field on every row.
Causal Intelligence Engine
Ask in plain English. The agent runs the analysis across your feedback and your revenue data, controls for segment and tenure, and returns the finding with an effect size, a confidence interval and a dollar figure attached.
On-Demand Intelligence Reports
Ask for the prioritization readout before planning starts and the agent builds it: ranked drivers, the revenue attached to each, charts, recommendations. Rerun it monthly and watch the ranking move as you ship.
System-Level Dimensions
Custom Dimensions per Business Objective
Multi-Dimension Orchestration
Output Validation - "hallucination" or drift check
Internal Vector Embeddings & Semantic Similarity
Dynamic Clustering & Theming
Multi-Dimensional Consolidation
Export ability to data warehouse
Generate causal reports, visualizations, and executive intelligence: on demand or scheduled
Plug into existing B.I tool of choice (Tableau, PowerBI, Hex)
Export via API to any warehouse (Snowflake, Databricks, BigQuery)
I can actually get the specificity that our product managers need — not just 'connectivity issues,' but which type, which product generation, all broken down. That level of detail is what makes this valuable
