SQL has a learning curve
The best AI code assistant for enterprise should fit your data sources, SQL requirements and review process, not just produce plausible code.
AI FOR DATA AND CODE
AI Code Assistant, Clear Queries. Reviewable Results.
Use Fluid AI as an AI code assistant to explore natural language to SQL, understand existing code and work with an AI dashboard from supplied spreadsheet data. Review the suggested query, calculations and interpretation before execution or use.
Illustrative workflow. People review outputs and make decisions.
FLUID AI / WORKSPACEILLUSTRATIVE
Explore service requests
Query preview · Verify against the source
Query.sqllegacy_rules.pyREAD ONLY PREVIEW
1
2
3
4
2
3
4
SELECT category, status
FROM service_requests
WHERE status <> 'closed'
ORDER BY category;
QUERY PREVIEWReview the query before running it against a configured source.
RESULT PREVIEWIllustrative rows · check source
CategoryStatus
Permit enquiryIn review
Service accessAwaiting detail
LEGACY CODE TAB Existing logic remains separate for inspection.
WORKING REQUEST
Show request category and status from the supplied data, then let me compare the result with the source table.
THE WORK BEHIND THE WORK01 02 03
Getting From Data to Understanding Takes Work
Legacy code is difficult to navigate
Existing code can require additional effort to understand.
Data needs context
AI business intelligence needs context. When evaluating an AI analytics platform, check how each view represents the supplied data.
Text to SQL, from Question to Query Review
Describe the task
Explain the query or information you need.
Generate or understand code
Use the SQL or code assistance workflow.
Explore data visually
Where supported, turn spreadsheet data into an interactive dashboard.
Check the result
Validate queries, data, calculations and interpretations before relying on them.
Available sources, integrations and output options depend on configuration. Review work before relying on it.
SQL AI and a First Step in Legacy Code Modernization
Use SQL AI to inspect suggested queries and explore data, or begin legacy code modernization by understanding existing behaviour. Fluid AI's demonstrated code support explains legacy code; it is not a promise of automated migration or production-ready rewrites.
MANUAL DATA EXPLORATION
Write, run and inspect
A data question can require familiarity with the schema, query syntax and the assumptions behind a result.
- Translate the question into a query that matches the available fields.
- Check filters, joins and calculations before interpreting a result.
- Compare outputs with source data and expected behaviour.
FLUID AI DATA WORK
SQL and code suggestions for review
AI can help explain data, prepare SQL or code suggestions, and support exploration of supplied information.
- Describe the question and inspect the suggested query before execution.
- Explore a view of the supplied spreadsheet or data.
- Validate calculations, assumptions and output against the original source.
Workflow fit, available sources and controls depend on configuration. Compare the approach against your task and review outputs before relying on them.
Natural Language to SQL and Code in Action
Code & SQL
Describe a task in plain English, get help generating SQL and explore explanations of legacy code.
Interactive Visualisation
Choose a dashboard type or describe a view, then filter and explore spreadsheet data in the browser.
AI Data Visualization, with Results You Can Check
Talk to your data
An AI SQL assistant helps translate a plain-English request into a proposed query for specialist review.
Legacy-code explanation
Ask for help understanding existing code.
AI data analysis
Create and explore browser-based dashboards from supplied spreadsheet data, then validate the results.
Dashboard choices
The AI data visualization demo offers seven dashboard types or a view described by the user, with browser-based filtering.
Deployment considerations
The Code & SQL material describes on-premise deployment; see existing deployment options.
No output is guaranteed to be complete or accurate. Check relevant source material and results.
Ask a Data Question Without Starting With SQL Syntax
AI SQL and legacy code for government and PSU teams should use approved datasets and code, confirm access controls and review suggestions before execution. For a data question, inspect the SQL, explore the view and validate calculations against the source table.
State the data question
Describe the fields or patterns you want to examine in the supplied data.
Review the query or code
Check the logic and assumptions before running or applying a suggestion.
Verify the result
Compare calculations and outputs with the source data before drawing conclusions.
Illustrative only. A person checks the relevant source, output and next step before it is used.
Your work. Your requirements.
Every organisation has its own security and governance requirements. Evaluate them against the proposed deployment and configuration.
Deployment shaped around your needs
Discuss hosting and deployment requirements with the Fluid AI team. Options depend on your environment and use case.
Access configured for the workflow
Review which datasets and code environments are in scope, who may access them, and how query execution and results are controlled in your configuration.
Reviewable work and context
Generated SQL is a starting point. Check the query, calculations and results against the underlying data before relying on them.
Security review with your team
Review architecture, data handling and security requirements with Fluid AI during evaluation.
FAQ
Frequently Asked Questions
Answers about ai sql, data analysis & legacy code.
START A CONVERSATION
Make Data and Code Easier to Work With
Explore AI assistance for SQL, legacy code and interactive data visualisation.
FLUID AI / AI SQL, DATA ANALYSIS & LEGACY CODE