Dexter is described as an autonomous agent tailored for deep financial research: you pose complex financial questions (for example, about a company’s revenue growth or financial ratios) and Dexter breaks them down into structured research tasks, fetches relevant real-time data (e.g. income statements, cash flows), performs analysis, and returns data-backed answers. It uses a multi-agent architecture with components such as a planning agent (to decompose queries), an action agent (to run tasks & fetch data), and self-validation mechanisms: after getting results, Dexter checks its own outputs and refines them until it is confident about its answer. This means it's more than a simple script — it’s a research assistant that loops through analysis steps until convergence.
Features
- Automatic decomposition of complex financial queries into research tasks
- Autonomous data gathering from live financial datasets (income statements, cash flows, etc.)
- Multi-agent architecture (planning agent + action agent) for structured, modular execution
- Self-validation and iterative refinement to ensure confidence in results
- Support for natural-language queries to enable easier user interaction
- Uses modern runtime (Bun) and leverages external APIs (financial data + reasoning) for flexibility