# Dexter — Autonomous Agent for Deep Financial Research

> An open-source autonomous AI agent that performs multi-step financial research, analyzing earnings, filings, and market data to produce structured investment reports.

## Install

Save as a script file and run:

# Dexter — Autonomous Agent for Deep Financial Research

## Quick Use
```bash
git clone https://github.com/virattt/dexter.git
cd dexter && npm install
npm run dev
```

## Introduction
Dexter is an open-source autonomous agent designed for deep financial research. It chains together multiple LLM-powered analysis steps — from data gathering to report writing — to produce structured investment research that would normally take an analyst hours.

## What Dexter Does
- Autonomously researches companies using public financial data and filings
- Chains multi-step analysis: data retrieval, financial modeling, comparison, and report generation
- Produces structured research reports with quantitative backing
- Supports configurable research workflows and custom analysis templates
- Integrates with multiple LLM providers for the reasoning layer

## Architecture Overview
Dexter is a TypeScript application built around a directed acyclic graph of research steps. Each step is an autonomous agent node that performs a specific task (fetch SEC filings, analyze revenue trends, compare competitors) and passes structured output to downstream nodes. The orchestrator manages execution order, retries, and context sharing. A web UI lets users configure research targets and review generated reports.

## Self-Hosting & Configuration
- Clone the repository and install dependencies with npm
- Configure your LLM provider API keys in the environment file
- Set up financial data source credentials (SEC EDGAR is free)
- Customize research templates in the configuration directory
- Run the web interface locally on the default port

## Key Features
- Multi-step autonomous research pipeline, not single-prompt generation
- Structured output with citations and data references
- Configurable analysis templates for different research types
- Support for multiple LLM backends (OpenAI, Anthropic, local models)
- Web UI for configuring research targets and reviewing reports

## Comparison with Similar Tools
- **Bloomberg Terminal** — professional financial data platform; Dexter is open-source and focused on automated analysis
- **FinGPT** — fine-tuned financial LLM; Dexter is an agent workflow, not a single model
- **Langchain Financial Agents** — generic agent framework; Dexter is purpose-built for investment research
- **AlphaVantage + GPT** — manual API + prompt combo; Dexter automates the full pipeline

## FAQ
**Q: Does Dexter provide investment advice?**
A: No. It generates research reports as a tool for analysts. All output should be reviewed by a human before making investment decisions.

**Q: What financial data sources does it use?**
A: It primarily uses public data from SEC EDGAR, Yahoo Finance, and similar free sources.

**Q: Can I use local LLMs instead of cloud APIs?**
A: Yes. Dexter supports any OpenAI-compatible API endpoint, including local servers.

**Q: Is it suitable for real-time trading?**
A: No. Dexter is designed for deep research, not high-frequency or real-time trading.

## Sources
- https://github.com/virattt/dexter


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Source: https://tokrepo.com/en/workflows/asset-d4ee599e
Author: Script Depot