Project Overview

The Data Assistant Agent backend empowers business teams with end-to-end research capabilities: simply input keywords and receive structured insights. The system automatically orchestrates external data collection, integrates information from multiple sources, builds a queryable knowledge base, and exposes research progress, aggregated results, and intelligent Q&A via APIs.

Problems Solved

• Business, marketing, and operations teams manually collect, organize, and summarize information for research.
• Data from diverse sources varies in format, making it difficult to consolidate into a reusable knowledge base.
• Similar research requests are repeatedly executed without caching or reuse mechanisms.

Use Cases

• Market Research: Rapidly generate structured reports on brands, products, or topics.
• Customer Insights: Aggregate fragmented customer feedback into a natural-language-queryable knowledge base.
• Competitive Analysis: Periodically scrape public information to track and compare trend shifts.
• Intelligent Q&A: Directly answer team questions using already-archived materials.

Key Features

• Automatic reuse of similar historical tasks—reducing redundant data collection costs.
• Normalization of multi-source data into a unified schema before ingestion.
• Natural-language querying of the knowledge base—enabling business users to skip raw documents entirely.
• Full traceability: research progress, summary outputs, and source data are all auditable and layered.

Tech Stack

Python + PostgreSQL + industry-leading LLMs and retrieval-augmented generation (RAG) capabilities.