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Case 032026Full Stack AI Engineer

Sociolyte Social Media Automation

AI-powered social media automation

Sociolyte emerged from a challenge: social media shouldn't consume your day. Fueled by the ambition to turn content creation from a chore into an automated art, I crafted a platform where AI doesn't just assist - it orchestrates your entire social presence across platforms.

PythonFastAPIDockerNginxCustom Diffusion ModelSQLite+1
01

94% brand compliance on AI-generated images

02

50% faster campaign deployment

03

85% reduction in manual content operations

SnapshotAt a glance

Full Stack AI Engineer

5 months

Key Components
Celery Task Queue
Redis Broker
Multi-platform OAuth
AI Content Pipeline
Rate Limit Handler
Outcomes

94% brand compliance on AI-generated images

50% faster campaign deployment

85% reduction in manual content operations

99.9% uptime with Nginx load balancing

42% latency reduction

Technologies Used

7 Technologies Integrated

Python
FastAPI
Docker
Nginx
Custom Diffusion Model
SQLite
Google Gemini API
85%

Impact

Key Features

Feature Implementation

5 Features
88%
Feature CoverageProject Scope

Project Vision

Automate the entire social media lifecycle using AI.

Core Process

The process of Developing it.

Built modular AI pipelines and deployed with Docker + Nginx load balancer.

Build notesWhat I built

04
  1. Custom Diffusion Image Generation Model

    Constructed a custom image generation model fine-tuned on company branding, achieving a 94% brand compliance score by utilizing Google Gemini API to optimize user prompts for stylistic consistency.

  2. Production Content Automation Engine

    Designed a production-grade content engine featuring speech-to-text input for rapid drafting and scheduling pipelines, accelerating campaign deployment by 50%.

  3. Secure Backend and Infrastructure

    Deployed a secure backend with role-based authentication (RBAC) and Dockerized microservices, reducing manual content operations by 85% while ensuring strict data privacy and access control.

  4. High-Availability Load Balancing and Maker-Checker RBAC Workflow

    Configured an Nginx load balancer with upstream failover across FastAPI instances, achieving 99.9% uptime and reducing latency by 42%. Deployed a KPI-driven Maker-Checker RBAC workflow, improving publishing accuracy by 60% and eliminating unauthorized deployments.

Inspiration
Manual social media workflows were inefficient and inconsistent.

Features

  • AI-generated text & image content
  • Multi-platform posting automation
  • A/B content variation
  • Hashtag & tone optimization
  • Engagement analytics

Challenges

  • Platform-specific constraints
  • Rate limiting
Solution

Adaptive posting logic with production-grade backend.

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