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Answer retail analytics questions with natural-language reasoning over SQL and RAG.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Retail Analytics Agent" yet — see the docs or source repo.
Analyze store performance in East China over the last 30 days. Rank stores by revenue, order count, and average order value, and identify the best and worst performers with possible reasons.
A ranked store performance analysis with key anomalies, trend summaries, and likely explanations.
Why did ready-to-drink coffee sales decline month over month this month? Analyze using sales volume, inventory, promotions, and customer feedback.
An explanation of the main drivers behind the category decline using both structured data and text evidence.
Based on the last 8 weeks of regional sales, stockout rates, and holiday trends, provide restocking and promotion recommendations for key products next week.
A regional action list with product priorities, restocking levels, promotion ideas, and brief rationale.
Connect AI clients to retail customer, inventory, sales, order, and support workflows.
Turn natural language into PostgreSQL queries with readable, context-aware answers.
Retrieve relevant context and metadata from Qdrant using natural language queries.
Intelligent RAG tool that chooses between private knowledge and web search.
Query and manage Microsoft SQL Server databases with natural language.
Index documents and retrieve relevant context for better LLM responses.