Prompt-Based Business Intelligence System

1. The Operational Challenge: Analytics Turnaround Lag

In growing technology and fintech startups, product managers and executive leaders require immediate quantitative answers to operational queries: *\"What was the default rate on 36-month two-wheeler loans last month in Delhi compared to Mumbai?\"* or *\"Which affiliate partner is driving the highest volume of drop-offs during KYC verification?\"*

Because querying relational production databases requires structured SQL and familiarity with database schemas, every question turns into a Jira ticket queued for the data engineering team, creating multiday turnaround delays for routine business decisions.

2. Architectural Design & Security Sandboxing

[ Executive Natural-Language Prompt ]
               │
               ▼
   [ Schema Metadata Injector ] ───► Sanitized DB Table & Column Schema
               │
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   [ LLM Translation Engine ] ────► Generate Audited Read-Only SQL Query
               │
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   [ Security Validator & Linter ] ─► Block DROP/DELETE/INSERT/UPDATE;
               │                     Enforce Strict Limit Clamping & Timeouts
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   [ Read-Only Sandbox Execution ] ─► Execute Against Analytics Replica
               │
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   [ Dynamic Visualizer & Summary ] ─► Render Clean Data Table & Plotly Charts

Security & Determinism Guardrails

• Zero Write Access: Strict read-only database user credentials and AST (Abstract Syntax Tree) SQL linting prevent any accidental state mutation or data leaks.
• Schema Embedding: Embeds table relationships, foreign key constraints, and business acronyms into the context prompt to ensure exact join logic across normalized databases.
• Explainable SQL: Outputs the executed SQL alongside the visual chart so analysts can verify query logic before relying on calculations.

3. Results & Business Value

The system democratized access to data, freeing data engineers from answering repetitive operational requests while empowering leadership with immediate insights.

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