Sept 2024 - Sept 2025
engineer
ai
agents

The Challenge

Financial workflows are complex, time-consuming, and require expertise across multiple domains. Professionals spend hours gathering data from various sources, analyzing information, and making decisions. We wanted to revolutionize finance by automating these key workflows while maintaining accuracy and compliance.

My Approach

We built a suite of specialized tools that could pull relevant content and data for any financial question. The breakthrough was creating an agent that could choose which tools to use and parallelize actions to gather different data sources simultaneously, then analyze everything it had collected.

The Solution

I built the entire product from 0-1 in a couple of months, focusing on a custom UX that visualized the agent's decision-making process. Using React Flow, I created a tree-like interface showing each tool call as nodes, making the agent's reasoning transparent. The system could parallelize actions and take multiple analysis paths simultaneously—a new paradigm for agent capabilities.

Impact & Results

Essential AI transformed how financial professionals work, reducing research time from hours to minutes. The visual workflow representation built trust by showing exactly how decisions were made. The parallel processing approach set a new standard for agent efficiency in complex domains.

Key Learnings

Multi-agent systems require entirely new UX paradigms. Users need to understand not just what agents are doing, but how and why they're doing it. Visualization of agent reasoning is crucial for building trust in high-stakes financial decisions.

Product Demo