Every screenshot below is a real IQVigilant answer to a plain-language question — charts, conversations, and analytical insights, all generated from your data model's metadata with no code, no data engineering, and no guessing.
Proportional charts that show part-to-whole relationships at a glance.
Planned cost per task grouped by status, rendered as a donut chart.
Payment amounts grouped by staff member name.
Actual work hours across tasks grouped by project.
Film replacement cost grouped by rating category.
Compare magnitudes across categories with bar and stacked layouts.
Planned cost per task grouped by priority level.
Payment amounts grouped by customer last name.
Actual progress per task stacked by priority.
Boxplot and bubble charts to explore data distributions and relationships.
Distribution of task progress across priority levels.
Distribution of film lengths across categories.
Film rental rates grouped by rating.
Track change over time and cumulative movement.
Task work hours trend grouped by project.
Work hours by task status as a waterfall chart.
Rental duration by film rating category.
Film length distribution grouped by rating.
Multi-sentence conversations that mix queries, charts, and ML-style learning.
ML-style queries that ask the engine to understand and summarize data relationships.
Open-ended questions answered with data-driven insights. Deterministic agents analyze your data and return plain-language conclusions.
Deep analytical questions answered with data-driven insights from your real data.
Cross-domain reasoning spanning analytics, external APIs, and real-world context.
IQVigilant plugs into your database and delivers answers like these — instantly, with zero data engineering.