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🚧 AI-Native Engineering Resource Planning System (ERPS)

Public SDK, Architecture Contracts & Integration Layer


⚠️ PROJECT STATUS: PRE-ALPHA / ACTIVE DEVELOPMENT
This platform is under heavy construction. The architecture is stable, but APIs, data models, and infrastructure integrations are subject to breaking changes.
Not production-ready.


🧠 What is ERPS?

ERPS (Engineering Resource Planning System) is an AI-native engineering control plane designed to orchestrate, govern, and optimize complex engineering workflows using:

  • Multi-agent AI execution
  • Deterministic governance & policy enforcement
  • Distributed workflow orchestration
  • High-fidelity telemetry & observability
  • Secure identity propagation

Unlike traditional business ERP systems, ERPS acts as an intelligent operating system for engineering processes, enabling:

  • Safe AI automation
  • Enterprise-grade policy enforcement
  • Distributed workflow control
  • Autonomous engineering pipelines

🎯 Purpose of erps-platform-sdk

This repository contains the public interface contracts, SDKs, architecture definitions, and integration patterns for the ERPS platform.

It does NOT contain private core engines, orchestration runtimes, or governance logic.


🏗️ System Architecture

ERPS is designed as a distributed, modular, policy-driven execution platform.

Architecture level Overview

 
 ┌──────────────────────┐
            │      Clients         │
            │ (API / SDK / UI)     │
            └─────────┬────────────┘
                      │
                      ▼
            ┌──────────────────────┐
            │     API Gateway      │
            │ (Ingress + Routing)  │
            └─────────┬────────────┘
                      │
                      ▼
            ┌──────────────────────┐
            │   Access Control     │
            │  (AuthN / RBAC /     │
            │   Identity)          │
            └─────────┬────────────┘
                      │
                      ▼
            ┌──────────────────────┐
            │   Step Management    │
            │ (Workflow Engine)    │
            └─────────┬────────────┘
                      │
                      ▼
    ┌─────────────────────────────────────┐
    │         Rules Engine                │
    │ (Deterministic Governance Layer)   │
    └─────────┬──────────────┬────────────┘
              │              │
              ▼              ▼
 ┌───────────────────┐   ┌────────────────────┐
 │ Knowledge Engine  │   │ AI Orchestration   │
 │  (RAG + Memory)   │   │ (Multi-LLM Router) │
 └─────────┬─────────┘   └─────────┬──────────┘
           │                       │
           ▼                       ▼
    ┌─────────────────────────────────────┐
    │     Reporting & Analytics Engine    │
    │ (Telemetry, Cost, Quality, Metrics)│
    └───────────────┬─────────────────────┘
                    ▼
            ┌──────────────────────┐
            │     Data Layer       │
            │ (DB / Cache / Store) │
            └──────────────────────┘

🔄 Request Lifecycle

  1. Ingress: API Gateway receives request
  2. Validation: Access Control verifies identity and permissions
  3. State Tracking: Step Manager creates workflow & tracks state
  4. Governance (Pre): Rules Engine enforces enterprise policies
  5. Contextualization: Knowledge Engine retrieves context & embeddings
  6. Execution: AI Orchestrator routes tasks to optimal LLM(s)
  7. Governance (Post): Output validation & enforcement
  8. Auto-Correction: AI-assisted remediation
  9. Telemetry: Analytics engine captures metrics & learning signals

🧠 Core Architectural Principles

  • Domain-Driven Design (DDD): Strict separation of domain boundaries
  • Deterministic Governance: AI outputs must satisfy enterprise policies
  • Zero Silent Failures: All failures traced, categorized, and handled
  • Streaming-Safe Analytics: Deterministic telemetry & replay-safe design
  • Multi-Model Arbitration: Intelligent routing across multiple LLM providers

🗺️ Development Roadmap & Current Status

We are building this platform module by module, enforcing strict isolation and deterministic behavior.

🧠 Core Execution

Module Description Status
ai_orchestration/ Multi-LLM routing, async execution, provider arbitration ✅ Completed
step_management/ Distributed workflow engine, DDD aggregates, lifecycle FSM ✅ Completed

🛡️ Governance & Security

Module Description Status
rules_engine/ Deterministic policy evaluation, enforcement, audit trails ✅ Completed
access_control/ AuthN, RBAC/ABAC, identity propagation 🏗️ Planned

📊 Intelligence & Data

Module Description Status
knowledge_engine/ RAG, embeddings, auto-correction, trust modeling ✅ Completed
reporting_analytics/ Telemetry, cost/latency metrics, anomaly detection ✅ Completed
data_layer/ Unified persistence interface, adapters ✅ Completed

🚪 Infrastructure

Module Description Status
main.py Central bootstrap & DI wiring ✅ Completed
api_gateway/ Async ingress & routing 🏗️ Planned
utils/ Shared helpers ⏳ In Progress

🖥️ User Interface

Module Description Status
ui_ux/ Dashboards, approval workflows, visualization 🏗️ Planned

📁 Public Repository Structure

 erps-platform-sdk/ ├── interfaces/       
 Public interface contracts ├── sdk/             
 Client SDKs (Python, JS, Go) ├── examples/         
 Workflow & integration demos ├── architecture/    
 Design docs & diagrams ├── docs/             
 Getting started, config, roadmap ├── LICENSE.md 
 └── README.md

🔐 Open-Core Architecture

This project follows a controlled open-core strategy.

Public:

  • Architecture
  • Interfaces
  • SDKs
  • Examples
  • Documentation

Private:

  • Core orchestration engines
  • Workflow runtime
  • Governance execution logic
  • Identity engine
  • Infrastructure integrations

📜 License

This project is released under a Source-Available License.

Free for:

  • Personal use
  • Educational use
  • Research & experimentation
  • Non-commercial evaluation

Commercial usage requires a paid license:

  • SaaS platforms
  • Enterprise internal production
  • Hosted AI services
  • Redistribution

See LICENSE.md.


🚀 Target Users

  • Platform engineers
  • AI infrastructure developers
  • Workflow automation architects
  • Distributed systems engineers
  • Enterprise AI integrators

🧪 Development Disclaimer

This platform is:

  • Pre-alpha
  • Under heavy development
  • Architecture-stable
  • API-unstable

Expect breaking changes.


🙏 A Note from the Author

This is my first open-source engineering platform.
I tried to build something ambitious and robust.
I promise to keep improving it continuously.


                                          Thank you for visiting


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Public Interface, SDK, and Architecture Contracts for the ERPS Control Plane

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