# Fovea AI Query Builder — Write Complex Queries in Plain English

Stop translating business questions into SQL. Describe what you need, and Fovea generates a validated, context-aware query — respecting your data catalogue, governance rules, and schema relationships automatically.

1. **Instant dashboards -** Turn raw data into actionable dashboards with natural language prompts
2. **Seamless automation -** Automate your workflows with the help of Fovea
3. **Insights on-demand -** Ask Fovea questions about your data and get insights instantly
[Try Fovea Live — No signup needed](/platform/fovea-agentic-ai/try-fovea)

## Sign up for a 30-day free trial

AI Query Builder

## Build Complex Queries Using Plain English

Stop translating business questions into SQL syntax. Describe what you need in natural language and Fovea generates a validated, context-aware query — respecting your data catalogue, governance rules, and schema relationships automatically.

[See it in action](/book-a-demo)

Fovea AI Query Builder

// Your question

"Show me total revenue by product category for the last 6 months"

// Generated SQL

SELECT
  c.category_name,
  SUM(o.revenue) AS total_revenue,
  COUNT(o.id)    AS order_count
FROM orders o
JOIN products p ON p.id = o.product_id
JOIN categories c ON c.id = p.category_id
WHERE o.order_date >= CURRENT_DATE
      - INTERVAL 6 MONTH
GROUP BY c.category_name
ORDER BY total_revenue DESC;

Query validated · Catalogue context applied · Ready to run

## From Question to Query in Seconds

The AI Query Builder removes the SQL bottleneck so anyone on your team can access the data they need, right when they need it.

### Reduce Dependency on SQL Knowledge

Business users can query data directly without involving engineers. Plain-English prompts become production-ready SQL in seconds.

### Speed Up Report Creation & Dashboard Building

Stop waiting for analyst queues. Generate the underlying query for any KPI, chart, or table instantly — iterate in real time.

### Auto-Identify Filters, Metrics, Dimensions & Date Ranges

Fovea reads your data catalogue to automatically map the right fields, apply the right filters, and scope to the right time window.

### Pipeline Integration

Embed generated queries directly into Infoveave data pipelines. AI-authored queries feed dashboards, automations, and scheduled reports.

## How the AI Query Builder Works

Four steps from natural language to a validated, runnable query — no SQL knowledge required.

1

### Enter Your Question

Type your question in plain English — e.g., “What were total sales by region last quarter?”

2

### Fovea Reads Context

The AI checks your data catalogue — schemas, relationships, approved metrics, and governance rules.

3

### Query Generated & Validated

A syntactically correct, context-aware SQL query is generated and validated before being returned to you.

4

### Run, Refine, or Embed

Execute the query immediately, ask Fovea to refine it, or embed it into a dashboard or pipeline.

1

### Enter Your Question

Type your question in plain English — e.g., “What were total sales by region last quarter?”

2

### Fovea Reads Context

The AI checks your data catalogue — schemas, relationships, approved metrics, and governance rules.

3

### Query Generated & Validated

A syntactically correct, context-aware SQL query is generated and validated before being returned to you.

4

### Run, Refine, or Embed

Execute the query immediately, ask Fovea to refine it, or embed it into a dashboard or pipeline.

## Built-In Context Awareness

Fovea doesn't generate generic SQL. Before writing a single line, it reads your data catalogue — understanding your exact table structure, approved metric definitions, field relationships, and governance rules. The result is a query that's correct for _your_ environment, not just syntactically valid in the abstract.

### What the catalogue provides:

* **Schema awareness** — correct table and column names, data types, and nullability
* **Relationship mapping** — foreign keys and join paths resolved automatically
* **Metric definitions** — "revenue" means the same thing everywhere; approved calculations applied consistently
* **Governance rules** — restricted fields excluded, row-level filters enforced

### Example — NMI validation

// Before generating, Fovea checks:

[Catalogue Check]
  Table: meter_readings   ✓ exists
  Column: nmi             ✓ indexed
  Column: read_date       ✓ date type
  Governance: nmi_masked  ✓ applied
  Join: sites → meters    ✓ resolved

[Generated Query — validated]
SELECT s.site_name,
       COUNT(r.id) AS readings
FROM meter_readings r
JOIN sites s ON s.nmi = r.nmi
WHERE r.read_date >= '2025-01-01'
GROUP BY s.site_name;

More than generation

## Beyond Query Generation

The AI Query Builder doesn't just write new queries from scratch. It's a full query companion — refine what you have, understand legacy SQL, and keep your data logic current as your business evolves.

* →**Refine existing queries** — add filters, change aggregations, or adjust date ranges just by describing the change in natural language
* →**Optimize for performance** — ask Fovea to rewrite a slow query using better indexing strategies, CTEs, or materialised views
* →**Explain any query in plain English** — paste unfamiliar SQL and get a clear, step-by-step explanation of what it does and why
* →**Modify on-the-fly** — change the grouping, swap metrics, or add a conditional in one conversational turn

### Explain Mode

Paste any SQL query. Fovea returns a plain-English explanation of every clause — ideal for onboarding new analysts or auditing legacy reports.

"Explain what this query does and flag any performance issues"

### Modify Mode

Already have a working query? Tell Fovea what needs to change and get an updated version in seconds — no syntax hunting required.

"Add a filter for the APAC region and break down by month instead of quarter"

## See It in Action

Real questions, real queries — generated by Fovea AI in a single prompt.

### Sales Performance by Region

Ask: “Show me total revenue and units sold per region for Q1 2025 compared to Q1 2024.”

Generated SQL

SELECT
  region,
  SUM(revenue)     AS total_revenue,
  SUM(units_sold)  AS total_units,
  YEAR(order_date) AS year
FROM sales_orders
WHERE YEAR(order_date) IN (2024, 2025)
  AND QUARTER(order_date) = 1
GROUP BY region, YEAR(order_date)
ORDER BY region, year;

### Inventory Below Reorder Threshold

Ask: “Which products are currently below their reorder point and haven't been restocked in 30 days?”

Generated SQL

SELECT
  p.product_name,
  i.current_stock,
  i.reorder_point,
  MAX(r.restock_date) AS last_restock
FROM inventory i
JOIN products p    ON p.id = i.product_id
LEFT JOIN restocks r ON r.product_id = i.product_id
GROUP BY p.product_name, i.current_stock, i.reorder_point
HAVING i.current_stock < i.reorder_point
   AND (last_restock IS NULL
        OR last_restock < CURRENT_DATE - INTERVAL 30 DAY)
ORDER BY i.current_stock ASC;

## Frequently Asked Questions

What is the Fovea AI Query Builder?

Do I need SQL knowledge to use the AI Query Builder?

How does context awareness work in the AI Query Builder?

Can the AI Query Builder work with queries I've already written?

## Ready to write your next query without writing SQL?

See how Fovea's AI Query Builder fits into your team's workflow. Book a personalised demo and bring your own data questions.

[Book a Demo](/book-a-demo)

Ready to see Infoveave in action?

Book a personalised demo with our data experts

[Book a Demo](/book-a-demo)

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