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Overview

The Vigilos AI agent is more than a chatbot. It’s an intelligent agent that learns your data, remembers context across conversations, and gets sharper with every question. It thinks through problems, not just translates words to queries. When you ask a question, the agent maps your intent to your semantic model’s business vocabulary, explores the live database schema, generates an optimized query, and returns results with an interactive visualization and natural language explanation.

How the Agent Works

When you ask a question, the agent follows a structured process to deliver accurate results:
1

Understand your question

The agent reads your question and maps it to your semantic model’s business vocabulary - entity names, column descriptions, relationships, and predefined measures. This ensures it interprets “revenue” or “active users” exactly the way your team defines them.
2

Explore the live schema

The agent fetches the current schema directly from your database to verify that tables and columns are up to date. This prevents errors from stale assumptions if your schema has recently changed.
3

Generate the query

Based on the complexity of your question, the agent generates either a structured query configuration using the built-in BI engine, or advanced SQL for complex analytical questions. The BI engine compiles configurations into optimized SQL for your specific database (PostgreSQL, ClickHouse, Snowflake, Redshift, or BigQuery).
4

Execute against your database

The generated query runs directly against your database through the encrypted connection. Vigilos acts as a pass-through - it sends the query and receives the result set.
5

Analyze and visualize

The agent examines the returned data, selects an appropriate chart type, and provides a natural language explanation of what it found - including key trends, outliers, and notable patterns.

Visual Builder vs. Advanced Queries

The agent selects the query generation approach based on question complexity:
ApproachUsed WhenExamples
Visual builderSimple aggregations with grouping, filtering, and sorting”Total revenue by country”, “Top 10 customers by order count”
Advanced SQLComplex analytical queries”Month-over-month growth rate”, “Running total of revenue”, “Customers who ordered in January but not February”
Advanced SQL mode supports the full power of your database engine, including window functions, Common Table Expressions (CTEs), subqueries, UNION, and complex JOIN patterns.
The visual builder produces a structured configuration with:
  • Dimensions - columns to group by
  • Measures - aggregations to compute
  • Filters - conditions to narrow results
  • Sorts - ordering rules
  • Limit - maximum number of rows
  • Chart config - chart type and display options

Chart Types

When the agent returns results, it selects an appropriate chart type:
Chart TypeBest For
BarComparing categories
Horizontal barLong category labels
Stacked barPart-to-whole comparisons across categories
LineTrends over time
AreaVolume trends over time
PieProportional distribution
FunnelSequential stage drop-off
MetricSingle KPI values
TableDetailed row-level data
Chart options include title, legend visibility, stacking, smoothing, area fill, custom colors, and value formatting (number, currency, or percent).

Model Selection

Vigilos supports two modes for the underlying AI model:
Vigilos provides and manages the AI models. You do not need to supply any API keys. This is the default and recommended option for most teams.

Conversation Context

The AI agent maintains full context within a conversation. This means you can:
  • Ask follow-up questions that reference previous results (“Now break that down by region”)
  • Refine queries incrementally (“Exclude returns from that total”)
  • Ask the agent to explain its approach (“Why did you use a window function?”)
  • Request different chart types (“Show that as a line chart instead”)
Each conversation is independent. Starting a new conversation resets the context.