You will get AI Automation Workflow with Decision-Making Capabilities
Project details
## The Problem
- Manual Content Overload: Teams spent hours analyzing, categorizing, and scheduling digital content across platforms.
- Lack of Real-Time Insights: No automated way to extract sentiment, intent, or entities from conversations.
- Scalability Bottlenecks : Existing tools couldn’t handle growing volumes of content or integrate with modern AI models.
- Decision-Making Gaps*: No structured feedback loop to refine content strategies based on user interactions.
## Tech Stack :
- Python + FastAPI (Backend)
- Groq /OpenAI (LLM Analysis)
- PostgreSQL/MongoDB (Data Storage)
- n8n (Workflow Automation)
- Docker + Kubernetes (Deployment)
### The Results
- Real-Time Insights : Instant sentiment/intent detection for 10K+ daily interactions.
- Scalable Automation : Handled 10x content volume without additional headcount.
- Data-Driven Decisions : Feedback loops improved content engagement by **25%** in 3 months.
### Easy Takeaways
1. Pilot with one content type before scaling.
2. Structured insights > raw data.
3. Connect LLMs to existing tools for quick wins.
- Manual Content Overload: Teams spent hours analyzing, categorizing, and scheduling digital content across platforms.
- Lack of Real-Time Insights: No automated way to extract sentiment, intent, or entities from conversations.
- Scalability Bottlenecks : Existing tools couldn’t handle growing volumes of content or integrate with modern AI models.
- Decision-Making Gaps*: No structured feedback loop to refine content strategies based on user interactions.
## Tech Stack :
- Python + FastAPI (Backend)
- Groq /OpenAI (LLM Analysis)
- PostgreSQL/MongoDB (Data Storage)
- n8n (Workflow Automation)
- Docker + Kubernetes (Deployment)
### The Results
- Real-Time Insights : Instant sentiment/intent detection for 10K+ daily interactions.
- Scalable Automation : Handled 10x content volume without additional headcount.
- Data-Driven Decisions : Feedback loops improved content engagement by **25%** in 3 months.
### Easy Takeaways
1. Pilot with one content type before scaling.
2. Structured insights > raw data.
3. Connect LLMs to existing tools for quick wins.
Machine Learning Tools
ChatGPT, pandas, PythonWhat's included $250
These options are included with the project scope.
$250
- Delivery Time 3 days
- Number of Revisions 2
- Model Validation/Testing
- Model Documentation
- Data Source Connectivity
- Source Code
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About Valerian
Python Developer & Solution Architect
69%
Job Success
Chisinau, Moldova - 2:45 am local time
Top qualified Python developer with 7+ years delivering production-grade software across Web development, Cloud Infrastructure, DevOps automation, and Data Engineering. I combine deep technical expertise with a solution-architecture mindset — I don't just write code, I design systems that scale.
My background spans RESTful API development, containerized micro-services (Docker, Kubernetes), GCP cloud solutions, and full-stack web applications using Flask, Fast-API, and Django. I have hands-on experience architecture integration layers, designing enterprise BCM frameworks for national-level institutions, and building AI/ML-powered pipelines.
- Python , API Development & Integration
- Flask / FastAPI / Django
- Google Cloud / BigQuery / App Engine
- Data Automation & Extraction
- PDF & DOCX Processing
- JavaScript / jQuery / HTML / CSS
- Linux Bash Scripting
- Pandas / SQLite3 / SQLAlchemy
- PyTest / Unit Testing
- Cloud Deployment / Vercel / GitHub
- UX / UI Development
- Code Review & Mentoring
SKILLS:
AI Strategy Development
Claude Code Implementation
Automation Tools
Creative Problem Solving
Business Process Optimization
WHY ME?
✅ Clean, maintainable code with tests and documentation
✅ Clear communication and regular updates
✅ On-time delivery
✅ Long-term thinking—solutions built to last
Steps for completing your project
After purchasing the project, send requirements so Valerian can start the project.
Delivery time starts when Valerian receives requirements from you.
Valerian works on your project following the steps below.
Revisions may occur after the delivery date.
Task description