Dexter

What Is Dexter

Dexter is an autonomous financial research agent built to think, plan, and learn like a professional analyst. It turns complex financial questions into structured research plans, pulls verified market data in real time, and iterates using self-validation. Designed for deep analysis, Dexter acts like a full research assistant capable of reading company financials, comparing firms, and surfacing insights from live datasets.

How To Use Dexter

1. Create an account
   Sign up and access the Dexter dashboard.
2. Connect data sources
   Add your OpenAI key and a Financial Datasets provider in Settings.
3. Choose a workflow
   Start with templates for KPI lookups, peer comparisons, cash flow reviews, or build a custom workflow.
4. Ask a question
   Example prompts:
   • What was Apple’s revenue growth over the last 4 quarters?
   • Compare Microsoft and Google operating margins for 2023.
   • Analyze Tesla cash flow trends over the past year.
5. Review the research plan
   Dexter shows the planned steps, sources, and checks before running.
6. Run and validate
   Execute the workflow. Dexter fetches data, analyzes results, and self-checks for accuracy.
7. Export and share
   Save a report as PDF or CSV. Pin findings to a project or share with your team.

Customize Dexter

Use the Settings panel to adjust limits such as maximum steps, per-task depth, and safety controls. Choose which models and data providers are preferred for different task types. Turn on audit trails to log every step and data citation.

Dexter Key Features

Intelligent task planning: Breaks down complex prompts into clear research steps.
Autonomous execution: Calls the right tools to gather current financial data.
Self-validation: Verifies calculations and refines results before final output.
Real-time market data: Pulls income statements, balance sheets, and cash flows.
Safety controls: Step limits and loop detection to prevent runaway tasks.
Modular architecture: Planning, action, validation, and answer modules working together.

Dexter Use Cases

Financial analysts: Automate comparisons, quality checks, and recurring reports.
Investors and traders: Get fundamentals with live, verifiable numbers.
Researchers and academics: Run deeper studies with transparent methods.
Fintech builders: Embed autonomous market intelligence into your product.

Dexter FAQ

Is Dexter open source?
Yes. It is available under the MIT License.

Which languages power Dexter?
Primarily Python with minor JavaScript components on the tooling side. The web app requires no code to use.

What data sources are required?
OpenAI for reasoning and a Financial Datasets provider for market and company data.

Does Dexter improve its own output over time?
Yes. The self-validation module reviews and refines findings before results are finalized.

Can I extend Dexter?
Yes. You can fork the repo, add modules, and contribute improvements.

What makes Dexter different?
Dexter plans its work, checks itself, and iterates until results meet quality criteria. It behaves like an autonomous research assistant rather than a simple chatbot.