AI & Agentic
QueryBot — Conversational Data Intelligence
A production-ready, commercially deployed conversational analytics engine that lets business users query enterprise data in plain language — Arabic or English — without writing a single line of SQL.
The Challenge
In most enterprises, business users are separated from their own data by a bottleneck: the data or analytics team. Every ad-hoc question becomes a ticket, a wait, and a slide deck. Existing BI tools require training and are not conversational — they still demand structured thinking about data. QueryBot was built to eliminate this gap entirely.
Our Solution
Cody designed and built QueryBot as a retrieval-augmented generation (RAG) system layered over enterprise data sources. Natural-language questions — in Arabic or English — are parsed by an LLM, translated into safe read-only database queries, and results are returned as a plain-language response with source attribution. The product is schema-agnostic with connectors for PostgreSQL, MySQL, BigQuery, and Snowflake, with a React frontend and NestJS backend hosted on AWS.
How We Did It
- RAG architecture with document ingestion pipeline and vector store indexing
- LLM orchestration layer (GPT-4 / Claude — configurable) with safe read-only query generation
- Arabic/English bilingual NLP pipeline with domain-specific prompt engineering
- Schema-agnostic connector layer — PostgreSQL, MySQL, BigQuery, Snowflake, API endpoints
- Role-based access control — users only see data their permissions allow, with full audit trail
Key Outcomes
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