orchid

Orchestration Layer for Controlled, Independent Deployments

Abstract

AI is fundamentally changing how quickly business and domain teams can create new logic, validations, and insights. In regulated environments, this new speed collides head-on with legacy systems, monolithic architectures and IT landscapes that were never designed for continuous AI-driven change.

This Repo contains a reference implementation for a talk on PyCon DE 2026. It presents an open, Python-based platform architecture that turns AI-driven pressure into an architectural advantage. Instead of embedding AI into existing monoliths, the platform introduces a central control layer that orchestrates independent, stateless apps—ranging from classical algorithms to AI agents—without binding them to specific infrastructure or legacy constraints.

The control layer, implemented using Python and optionally Django, provides workflow orchestration, security, tenant management, and self-service registration of new components. This allows domain teams to deploy AI agents—such as anomaly detection for regulatory reporting—within days, while IT retains governance, auditability, and operational stability.

The talk argues that AI will amplify architectural weaknesses—and shows why modular orchestration layers will become essential for AI-ready systems far beyond finance.

Overview planned architecture

graph TB
    subgraph orchid["Orchid Control Layer (Django 6)"]
        registry[Registry Service<br/>App & Agent Registration]
        orchestrator[Orchestrator<br/>Django Tasks + Workflows]
        security[Security & Tenant Mgmt<br/>Auth, Authorization, Isolation]
        audit[Audit Trail & Monitoring<br/>Logging, Metrics, Events]
        connectors[Data Connectors<br/>File, DuckDB, Parquet, S3]

        registry -.-> orchestrator
        security -.-> registry
        security -.-> orchestrator
        audit <-.-> orchestrator
        orchestrator <--> connectors
    end

    subgraph apps["Independent Stateless Apps"]
        agentA[Agent A<br/>AI-based Analysis]
        agentB[Agent B<br/>Rule-based Validation]
        classical[Classical Algorithm<br/>Traditional Logic]
    end

    subgraph storage["Shared Data Layer"]
        files[Shared Files<br/>Parquet, JSON, CSV]
        duckdb[(DuckDB<br/>Analytics DB)]
        s3[Object Storage<br/>S3 compatible]
    end

    orchestrator -->|"control (REST)<br/>/start /status /stop"| apps
    
    connectors <-->|"data flow"| storage
    apps <-->|"read/write data"| storage    
    apps -.->|"reports status"| audit
    
    style orchid fill:#e1f5ff,stroke:#0066cc,stroke-width:2px
    style apps fill:#f0f0f0,stroke:#666,stroke-width:1px
    style storage fill:#fff4e6,stroke:#ff9800,stroke-width:2px

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