Building a Policy-Governed Multi-Agent Financial Research Workflow with Omnigent
Policy-governed multi-agent workflows move from sandbox to finance: cost budgets and tool limits now baked into production research pipelines.
Why it matters
Demonstrates practical agent governance—cost caps, tool call limits, hierarchical delegation—applied to a real financial workflow. Shows how agents are moving from prototype to policy-constrained production use.
The key facts
10 to knowMulti-agent workflow with hierarchical delegation for financial text auditing
Hard governance policies: cost budgets and tool call limits enforced in production
Live exchange-rate data integration into agent pipeline
Runnable in isolated Python environment (Google Colab)
Agent framework: Omnigent
Omnigent framework for multi-agent workflows
Hierarchical agent delegation for financial text auditing
Hard governance policies: cost budgets and tool call limits
Live exchange-rate data integration
Google Colab implementation (accessible, reproducible)
Go to the source
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Publisher excerpt: In this tutorial, we demonstrate how to build and execute a multi-agent workflow with Omnigent in a secure, isolated Python environment. Learn to integrate live exchange-rate data, implement hierarchical agent delegation for financial text auditing, and apply hard governance policies—such as cost…