Agentic AI & Data Analysis

Sheet Chat — Conversational Data Analytics

Context: Enterprise Project· Role: AI Engineer / Architect· Status: Enterprise AI Feature

An agentic AI system that lets users query Excel and CSV files in natural language — analyzing data, charting, flagging quality issues, and explaining results.

Business Problem

Non-technical users regularly need to analyze spreadsheets but can't easily write SQL, build visualizations, check data quality, or interpret raw analytical output.

Users

Business users working with Excel and CSV data who need answers, charts and reports without a spreadsheet-analysis background.

Constraints

Multiple analytical needs, one interface Consistent shared state Non-technical end users Mixed file formats (Excel/CSV)

Solution

I built a LangGraph multi-node pipeline that classifies each request and routes it to a specialized path — SQL analysis over DuckDB, visualization, report generation, data-quality checks, semantic search, or a natural-language explanation of the result.

Architecture

Sheet Chat architecture: file ingestion, data inspection, intent classification, conditional routing to SQL/DuckDB, visualization or data-quality checks, then a natural-language explanation
File Ingestion
Data Inspection
Intent Classification
Conditional Routing
Specialized Node Execution
NL Explanation

Your Contribution

Designed
the LangGraph architecture and multi-node workflow.
Implemented
conditional routing and shared typed state across nodes.
Integrated
DuckDB for structured SQL analysis over spreadsheet data.
Built
visualization, report-generation and data-quality workflows, plus semantic search and NL explanations.

Technology Stack

Python LangGraph DuckDB FastAPI Semantic Search Data Visualization

Results

6
analytical workflows, one interface
Automated
reports and explanations
technical barrier to data analysis

Challenges & Trade-Offs

Flexible agents vs. deterministic workflows

Conditional routing lets the system pick the right specialized path per request instead of forcing one rigid pipeline — trading some predictability for coverage across very different analytical tasks.