DataClaw: An Autonomous Data Agent with Instant Messaging Integration

TL;DR

DataClaw is an autonomous data agent integrated into instant messaging platforms, enabling users to perform complex data tasks through natural language commands with minimal technical barriers.

Contribution

It introduces DataClaw, a novel IM-integrated autonomous data agent with a transparent reasoning engine, multi-tiered memory, and extensible skills for seamless data analysis.

Findings

Enables natural language data analysis within IM platforms.

Uses a transparent ReAct reasoning engine for decision-making.

Supports cross-session context preservation and extensibility.

Abstract

In daily life, there are many scenarios that people need to tackle data-related tasks, such as filling out forms, analyzing Excel files, and visualize data report. However, the tools available for these tasks often fragment, requiring users to switch between multiple applications and manually orchestrate steps like data processing, querying, and visualization. Moreover, these tools often assume a certain level of technical proficiency, creating barriers for non-technical users. To facilitate tacking daily data task, we present DataClaw, an autonomous data agent that integrates directly into familiar instant messaging (IM) platforms. By simply typing a natural language request in a chat interface, users enable DataClaw to autonomously plan and execute a complete analytical pipeline, delivering insights, charts, and reports directly back into the conversation. Under the hood, DataClaw is powered by a transparent ReAct reasoning engine, a multi-tiered memory system for cross session context preservation, and a pluggable skill architecture for on-the-fly extensibility. In this demonstration, attendees will interact with DataClaw via standard IM platforms to solve real-world data scenarios, experiencing how it serves as a highly capable personal data assistant.