DeepO3

In Development

TradingAgents

Orchestrating automated reasoning workflows for enterprise decision systems.

Overview

A multi-agent financial analysis framework that coordinates specialist AI roles to pressure-test strategies before execution.

Why We Built It

TradingAgents was built to prove our capability in LangGraph orchestration and advanced multi-agent LLM architecture. The system mirrors institutional trading roles and drives structured debate loops to improve reliability in high-stakes reasoning workflows.

Technology Stack

  • LangGraph
  • Multi-agent routing layer
  • Provider abstraction
  • Python orchestration services
  • LLM observability tooling

Core Capabilities

  • Role-based orchestration for fundamental, technical, sentiment, and risk agents
  • Structured multi-step debate loops to reduce blind spots in decisions
  • Provider-agnostic model routing across OpenAI, Anthropic, Google, and Ollama

DeepO3 Approach

Built to stay robust as you scale.

Step 01

Clarity First

We translate high-level business goals into clear software milestones with measurable outcomes.

Step 02

AI Systems Engineering

From RAG to multi-agent orchestration, we build practical AI stacks that hold up in production.

Step 03

Reliable Delivery

Clean code, stable architecture, and collaborative rollout support from concept through handover.