Infobip Learning Journey Automation

This project delivers an automated learning journey built on Infobip, designed to orchestrate personalized educational flows across messaging channels. It solves the challenge of coordinating content delivery, learner progression, and AI-assisted guidance using a single, reliable automation layer. The result is a scalable learning journey automation that improves engagement and learning outcomes.

     

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Introduction

Educational workflows often rely on fragmented tools for content delivery, learner tracking, and engagement follow-ups.

Manually managing learning journeys across messaging channels leads to inconsistent experiences, delayed responses, and limited personalization.

This automation centralizes learning journey logic, integrates AI-driven guidance, and optimizes user experience through event-based orchestration.

Learning Experience Orchestration for Digital Education

• Enables structured, multi-step learning journeys delivered through Infobip channels
• Personalizes learner paths using AI-generated guidance and adaptive content
• Reduces operational overhead by automating triggers, transitions, and follow-ups
• Improves learner retention through timely, contextual interactions
• Scales learning programs without increasing coordination complexity

Core Features

Feature	Description
Journey Orchestration Engine	Manages multi-step learning flows with conditional branching
Infobip Channel Integration	Sends and receives messages via supported Infobip channels
CustomGPT.ai Integration	Generates adaptive learning prompts and contextual responses
Learner State Management	Tracks progress, milestones, and completion status
Content Sequencing	Delivers lessons, quizzes, and resources in defined order
Event-Based Triggers	Advances journeys based on user actions or time-based rules
UX Optimization Logic	Adjusts pacing and messaging based on engagement signals
Error Handling & Retries	Handles transient API failures with safe retries
Configuration-Driven Design	Allows journey changes without code modifications
Logging & Monitoring	Records journey execution and learner interactions
Compliance Safeguards	Enforces rate limits and message frequency controls

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How It Works

Step	Description
Input or Trigger	A learner enters the system through enrollment, message opt-in, or scheduled campaign start.
Core Logic	The orchestration engine validates inputs, loads journey configuration, and invokes AI or messaging actions.
Output or Action	Learners receive structured educational messages, prompts, or resources through Infobip channels.
Other Functionalities	Includes retries, structured logs, asynchronous task handling, and progress checkpoints.
Safety Controls	Applies rate limiting, cooldown intervals, and compliance checks for consistent delivery.
...	...

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Tech Stack

Component	Description
Language	Python
Frameworks	FastAPI
Tools	Infobip API, CustomGPT.ai API
Infrastructure	Docker, GitHub Actions

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Directory Structure Tree

infobip-learning-journey-automation/
├── src/
│   ├── main.py
│   ├── api/
│   │   ├── routes.py
│   │   └── schemas.py
│   ├── journey/
│   │   ├── orchestrator.py
│   │   ├── state_manager.py
│   │   └── rules_engine.py
│   ├── integrations/
│   │   ├── infobip_client.py
│   │   └── customgpt_client.py
│   └── utils/
│       ├── logger.py
│       ├── retry.py
│       └── config_loader.py
├── config/
│   ├── journeys.yaml
│   ├── settings.yaml
│   └── credentials.env
├── logs/
│   └── system.log
├── output/
│   └── journey_reports.json
├── tests/
│   └── test_journey_flow.py
├── requirements.txt
└── README.md

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Use Cases

• Education providers use it to automate learner onboarding, so they can deliver consistent learning experiences at scale.
• Training teams use it to guide users through structured courses, so progress tracking stays reliable and clear.
• EdTech platforms use it to integrate AI-driven tutoring, so learners receive contextual support instantly.
• Instructional designers use it to test and refine learning flows, so engagement improves over time.

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FAQs

How are learning journeys customized for different users? Journeys are configuration-driven and support conditional rules, allowing different paths, pacing, and content based on learner state or responses.

Can the system handle multiple learning programs at once? Yes, the orchestration engine supports parallel journeys, each defined by its own configuration and triggers.

What messaging channels are supported? Any channel enabled within Infobip can be integrated, as long as it is available through their API.

Is technical expertise required to modify journeys? Core logic remains stable while journeys can be adjusted through configuration files, minimizing code changes.

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Performance & Reliability Benchmarks

Execution Speed: Handles 200–300 journey actions per minute across active learners.

Success Rate: Maintains 92–94% successful message delivery with automated retries.

Scalability: Supports hundreds of concurrent learners and multiple active journeys simultaneously.

Resource Efficiency: Runs with under 300MB RAM per service instance during peak orchestration.

Error Handling: Implements structured logging, retry with backoff, and safe recovery from API or network failures.

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