AlphaAgent workflows enable automated construction of complex strategies like market-neutral stat arb portfolios, integrating macro causality, technical analysis, factor models, hedging, backtesting, and stress testing—with natural language objectives, data connectors (REST APIs/SQL), customisable graphs, and auditable memos.

AlphaAgent supports agent creation, agent workspaces, and automated SQL database schema discovery with role-based access control (RBAC).

AlphaAgent in chat mode converts natural language requests into SQL queries, interactive charts, and scripts executed via its Python runtime.

AlphaAgent uses a supervisor agent to break down complex problems into discrete subtasks and assign them to specialist agents with clear objectives—all with built-in transparency and detailed reasoning throughout.