Subham Haldar
workno source

FurnishKaro AI Assistant — Dual-Agent LLM System

Sole developer, greenfield · Nov 2025 – Feb 2026

An AI assistant layer over an existing multi-tenant interior-furnishing SaaS platform, adding natural-language analytics and high-speed structured data entry.

Dual-agent architecture

Two task-specialized agents with separate prompts, tool sets and isolated ephemeral memory: one for autonomous zero-clarification data entry, the other for cautious analytics querying. Splitting them meant neither had to compromise its behaviour for the other's use case.

Natural language to SQL

The hard part here is backend, not prompting. Dynamic database schema introspection with a five-minute cache feeds query generation, and every generated query passes runtime security validation enforcing multi-tenant data scoping before it executes.

Guardrails

Client-side UUID validation before API mutations, pre-flight duplicate-entity checks, and agent-readable error messages that guide self-correction rather than failing opaquely.

Retrieval

A RAG pipeline over two Pinecone vector indexes with resumable embedding scripts and metadata-size fallback handling for large nested records.

Status

Discontinued before production deployment. The engineering is real; the product never shipped.

Built with

PythonFastAPILangChainLangGraphPineconeSQLAlchemyMySQLWebSocket