Anthony Linsday
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CASE STUDY // PROJECT ID: 0xTA2

Triton Agency

STATUS: PRODUCTION

Full autonomous AI-agent consulting platform with tool calling, GitHub repo automation, Google Drive file processing, and automated video conferencing meeting summarization.

Autonomous AI Agents Python / LangChain AWS ECS / Fargate GitHub REST API Whisper Speech Models Redis Queue
AGENT RESPONSE TIME < 1.2s
CONNECTED TOOL APIS 18+ Providers
DAILY AUTOMATIONS 10,000+ Tasks

// 01. System Architecture

Triton Agency was built to orchestrate multi-step LLM agents across diverse software platforms. Rather than relying on simple prompt engineering, Triton operates state machines hosted on AWS ECS Fargate that execute deterministic tool calls, pull tickets from GitHub and Jira, analyze codebases, run tests, and propose PRs.

// 02. Asynchronous Tool Execution Flow 

User Request / Webhook Event
    → Redis Bull Queue (Priority Queue)
        → Triton Orchestrator (AWS ECS Fargate Worker)
            → Agent Context & Memory Retrieval (PostgreSQL pgvector)
            → Tool Invocation (GitHub, Drive, Slack, ShotBotz)
            → Output Validation & Safety Filters
    → Realtime SSE Stream & Audit Log

// 03. Key Capabilities

  • Repository exploration: Automated code review, issue triage, and PR draft generation.
  • Meeting transcription & actionable item extraction powered by fine-tuned speech models.
  • Self-healing execution: Automatic error retry and parameter correction upon tool failure.
  • Strict SOC2-compliant credential vaulting via AWS Secrets Manager and IAM role assumption.