AI Solution

Building an AI Data Analyst Agent

The AI Data Analyst Agent is designed to act as a digital analyst — capable of querying business data, deriving actionable insights, and interacting with users via natural language. Built on a robust, modular data infrastructure, this agent leverages structured data, generative AI, and business context to deliver insights with 99%+ accuracy.

Core Components

1
Data Connectivity

MCP Context Servers for all data sources

2
AI-Powered SQL

Natural language to SQL generation

3
Insight Engine

Industry knowledge and analysis

4
Feedback Loop

Continuous learning and improvement

1. Data Connectivity via MCP Context Servers

Context-aware, modular connectors that interface with all relevant data sources:

Sources Supported:

  • SQL Databases (PostgreSQL, MySQL, MSSQL)
  • Cloud Warehouses (Redshift, BigQuery, Snowflake)
  • SaaS Applications (CRM, ERP, PoS via API)

Context Layering:

  • Metadata schemas and relationships
  • Business glossary terms
  • Column-level lineage and definitions
2. AI-Powered SQL Generation

Natural language-to-SQL pipeline with three core modules:

NLU Module
Parses user questions to extract intent, entities, and filters
SQL Generator
Uses GPT-4/Claude with data context and business metadata
Execution Layer
Runs queries and visualizes results in charts or plain English
3. Insight Engine Trained on Industry Knowledge

Goes beyond basic querying to generate domain-relevant insights:

  • Pre-trained on industry best practices and benchmarks
  • Trend detection and anomaly identification
  • Correlation analysis and forecasting
  • Risk flagging and recommendations

Key Capabilities

Natural Language Querying

Users ask questions in plain English and get accurate SQL + charts

Multi-Source Context

Pulls from multiple databases with full schema awareness

Insight Summarization

Goes beyond charts to explain trends, anomalies, and drivers

Domain Expertise

Trained on industry reports and KPI models

Feedback Integration

Continuously learns from user feedback and edge cases

Security & Governance

Honors row-level security, PII redaction, and usage monitoring

Expected Outcomes

Self-service decision-making for business users without SQL skills

Faster turnaround on insights — minutes instead of hours/days

Scalable analytics without proportional analyst headcount growth

Improved data literacy across the organization

Foundation for autonomous business monitoring & copilots

Ready to Deploy Your AI Data Analyst?

Transform your data analysis with our intelligent AI agent that understands your business context.