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.
- Instant dashboards - Turn raw data into actionable dashboards with natural language prompts
- Seamless automation - Automate your workflows with the help of Fovea
- Insights on-demand - Ask Fovea questions about your data and get insights instantly
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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.
// 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;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.
Enter Your Question
Type your question in plain English — e.g., “What were total sales by region last quarter?”
Fovea Reads Context
The AI checks your data catalogue — schemas, relationships, approved metrics, and governance rules.
Query Generated & Validated
A syntactically correct, context-aware SQL query is generated and validated before being returned to you.
Run, Refine, or Embed
Execute the query immediately, ask Fovea to refine it, or embed it into a dashboard or pipeline.
Enter Your Question
Type your question in plain English — e.g., “What were total sales by region last quarter?”
Fovea Reads Context
The AI checks your data catalogue — schemas, relationships, approved metrics, and governance rules.
Query Generated & Validated
A syntactically correct, context-aware SQL query is generated and validated before being returned to you.
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
The catalogue is what makes every query accurate. Learn how Fovea builds and maintains it — including AI-generated documentation, metadata enrichment, and live synchronisation.
Explore Context & Catalogue AwarenessExample — 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.”
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?”
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
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 DemoFrequently Asked Questions
What is the Fovea AI Query Builder?
The AI Query Builder is a Fovea capability that converts plain-English questions into validated SQL queries. It reads your connected data catalogue to understand schema, relationships, and governance rules — generating queries that are correct and ready to run without manual SQL authoring.
Do I need SQL knowledge to use the AI Query Builder?
No. The AI Query Builder is designed for business users and analysts who want accurate data queries without writing SQL. You describe what you need in natural language, and Fovea handles the technical translation automatically.
How does context awareness work in the AI Query Builder?
Fovea reads your data catalogue — table schemas, field definitions, relationships, approved metrics, and governance rules — before generating any query. The output uses the correct table names, join paths, and date scopes for your environment.
Can the AI Query Builder explain or modify existing SQL queries?
Yes. Paste an existing SQL query and ask Fovea to explain it in plain English, optimize it, add filters, or modify it based on new requirements — all through natural language instructions.
Is the AI Query Builder included in Infoveave plans?
Yes. The Fovea AI Query Builder is native to Infoveave's agentic analytics layer — included across plans with no separate SQL IDE add-on. Queries run against governed catalogue definitions with RBAC enforced on every generated statement.
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