You will get AI-based Video Content Generation
Rising Talent
Project details
I will build an AI-assisted video creation workflow that transforms scripts or images into short video clips. This includes scene structuring, visual generation or selection, voice narration, and final video assembly.
The system is designed to help teams create consistent video content efficiently, with clear control over each step of the process. Outputs are suitable for marketing, educational, or creative use.
This is a user-controlled workflow intended for legitimate content production and does not involve any deceptive or misleading practices.
The system is designed to help teams create consistent video content efficiently, with clear control over each step of the process. Outputs are suitable for marketing, educational, or creative use.
This is a user-controlled workflow intended for legitimate content production and does not involve any deceptive or misleading practices.
AI Algorithms
Transformer ModelAI Applications
AI Content Creation, AI Text-to-Image, AI Text-to-Speech, AI-Generated VideoAI Development Language
PythonAI Tools
Hugging Face, PyTorch, TensorFlowAI Models
DALL-E, GPT-3, LLaMA, Midjourney AI, Stable Diffusion, WhisperWhat's included
| Service Tiers |
Starter
$600
|
Standard
$1,500
|
Advanced
$3,000
|
|---|---|---|---|
| Delivery Time | 5 days | 11 days | 20 days |
Number of Revisions | 1 | 1 | 1 |
AI Model Integration | |||
Batch Normalization | - | - | - |
Database Integration | - | - | - |
Detailed Code Comments | - | - | - |
Image Upscaling | - | - | - |
MLOps | - | - | |
Model Deployment | - | ||
Model Documentation | - | ||
Model Monitoring | - | - | - |
Model Testing & Optimization | - | - | |
Model Tuning | - | - | - |
Natural Language Processing | - | - | - |
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | - | ||
Setup File | |||
Source Code |
About Fariha
Production AI Engineer | Computer Vision & LLM Systems That Ship
Lahore, Pakistan - 1:18 pm local time
Most projects I work on fall into two areas:
(1) Computer Vision systems (detection, segmentation, classification, video)
(2) LLM/RAG document intelligence (ingestion, retrieval, guardrails, structured outputs, agents)
If you are building something real, I can help you design and ship it properly.
⭐ Key Achievements
• Multimodal Video Pipeline: Built an automated system (script → visuals → TTS → lip-sync → video), reducing manual video production effort and enabling scalable content generation.
• Biotech Computer Vision: Improved microscopy detection accuracy by 13% in production, deploying a system actively used by 100+ users.
• Detection & Segmentation Pipelines: Built YOLO/OpenCV-based systems for satellite imagery, sports analytics, and inspection, improving detection reliability across real-world scenarios.
• LLM Systems: Built production LLM pipelines (Legal Risk Analyzer, agentic planners) that convert unstructured inputs into structured, actionable outputs (JSON) for downstream automation.
⭐ What I Can Help You With
• Computer Vision: Detection, segmentation, classification, tracking, video analytics(YOLO, OpenCV)
• LLM / RAG & Agents: OpenAI, Ollama, LangChain, embeddings, structured outputs, guardrails
• End-to-End AI Pipelines: data → model → API → deployment (FastAPI, Docker, AWS/GCP)
• Automation: n8n workflows for AI-driven pipelines and integrations
⭐ Tech Stack
• Languages & Frameworks: Python, PyTorch, TensorFlow
• Computer Vision: YOLO (v5/v8/v11), OpenCV, SAM; detection, segmentation, tracking
• LLM Stack: OpenAI, Ollama, LangChain, RAG, FAISS/Chroma
• Infrastructure: FastAPI, Flask, Docker, AWS/GCP, Streamlit, n8n
⭐ Why You Should Work With Me
• Production-first mindset: systems designed to run reliably, not just demos
• End-to-end ownership: from data to deployed API
• Focus on measurable impact: accuracy, reliability, and usability improvements
• Clear communication and fast iteration
Tell me what you are building, and I will help you turn it into a working system!
Steps for completing your project
After purchasing the project, send requirements so Fariha can start the project.
Delivery time starts when Fariha receives requirements from you.
Fariha works on your project following the steps below.
Revisions may occur after the delivery date.
Client purchases the project and sends requirements.
Client gets a workflow diagram
The diagram will show exactly what will be implemented and delievered