Natural Language → SQL
Convert plain-English questions into SQL queries with AI assistance.
AI NexQuery lets you query databases, analyze documents, run machine learning workflows, and turn natural-language questions into useful data insights.
SELECT product, SUM(revenue)
FROM sales
GROUP BY product
ORDER BY SUM(revenue) DESC;
MySQL · ready to run
AI identified the strongest contributors and summarized the trend from the query result.
● Analysis completeOne focused workspace for natural-language SQL, document retrieval, AI-assisted analysis, machine learning and visualization.
Convert plain-English questions into SQL queries with AI assistance.
Work with MySQL and Microsoft SQL Server through a natural-language workflow.
Analyze database results and surface useful patterns, summaries and insights.
Ask questions across PDF, DOCX and TXT documents using AI-powered retrieval.
Use LangChain and FAISS-powered retrieval to find relevant document context.
Run supported machine-learning workflows without manually building every pipeline.
Turn results into understandable charts and visual data insights.
Supabase Authentication and Row-Level Security support controlled application access.
Move from a question to the right data workflow—SQL generation, retrieval, analysis or machine learning.
Translate natural-language intent into readable SQL and refine the query before execution.
Retrieve relevant document context and answer questions across supported file types.
Turn query outputs into useful summaries, patterns and visual insights.
Explore KMeans, PCA and Isolation Forest workflows through a focused interface.
Make complex results easier to understand with concise AI-assisted explanations.
Work with supported database structures while keeping the interaction natural and focused.
Go from a plain-English question to AI-assisted SQL, execution and understandable results.
Ask questions such as “Which products generated the highest revenue this quarter?” and use AI-assisted SQL generation to explore the result.
SELECT product, SUM(revenue) AS revenue
FROM sales
WHERE quarter = 'Q2'
GROUP BY product
ORDER BY revenue DESC;Upload PDF, DOCX or TXT documents and ask questions using LangChain + FAISS-powered retrieval/RAG.
Use a focused ML workspace for three supported workflows: clustering, dimensionality reduction and anomaly detection.
AI NexQuery uses application-level authentication and access controls without making exaggerated security claims.
The core workflow connects AI understanding with supported SQL, retrieval and machine-learning operations.
AI NexQuery was designed and built end-to-end as an individual developer, combining Python, Gemini AI, SQL, LangChain, FAISS and secure application architecture.
AI NexQuery is an AI-powered data intelligence platform for natural-language SQL, database analysis, document Q&A, RAG, machine learning workflows and data visualization.
AI NexQuery supports MySQL and Microsoft SQL Server.
Yes. It can convert natural-language questions into SQL and help users understand the generated query.
Yes. AI NexQuery supports questions over PDF, DOCX and TXT documents through an AI-powered retrieval workflow.
Document Q&A lets you ask questions about supported documents and retrieve relevant context using LangChain and FAISS-powered RAG.
ML Studio is the machine-learning workspace for supported workflows including KMeans, PCA and Isolation Forest.
The supported workflows are KMeans clustering, PCA dimensionality reduction and Isolation Forest anomaly detection.
The product uses Supabase Authentication and Row-Level Security for controlled application access.
AI NexQuery is available through the Microsoft Store.
Explore AI NexQuery and turn natural-language questions into data-driven insights.
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