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.
AI Query Builder
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.
// 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;The AI Query Builder removes the SQL bottleneck so anyone on your team can access the data they need, right when they need it.
Business users can query data directly without involving engineers. Plain-English prompts become production-ready SQL in seconds.
Stop waiting for analyst queues. Generate the underlying query for any KPI, chart, or table instantly — iterate in real time.
Fovea reads your data catalogue to automatically map the right fields, apply the right filters, and scope to the right time window.
Embed generated queries directly into Infoveave data pipelines. AI-authored queries feed dashboards, automations, and scheduled reports.
Four steps from natural language to a validated, runnable query — no SQL knowledge required.
Type your question in plain English — e.g., “What were total sales by region last quarter?”
The AI checks your data catalogue — schemas, relationships, approved metrics, and governance rules.
A syntactically correct, context-aware SQL query is generated and validated before being returned to you.
Execute the query immediately, ask Fovea to refine it, or embed it into a dashboard or pipeline.
Type your question in plain English — e.g., “What were total sales by region last quarter?”
The AI checks your data catalogue — schemas, relationships, approved metrics, and governance rules.
A syntactically correct, context-aware SQL query is generated and validated before being returned to you.
Execute the query immediately, ask Fovea to refine it, or embed it into a dashboard or pipeline.
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.
// 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
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.
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"
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"
Real questions, real queries — generated by Fovea AI in a single prompt.
Ask: “Show me total revenue and units sold per region for Q1 2025 compared to Q1 2024.”
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;
Ask: “Which products are currently below their reorder point and haven't been restocked in 30 days?”
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;See how Fovea's AI Query Builder fits into your team's workflow. Book a personalised demo and bring your own data questions.
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