You will get a AI face recognition system for real time security and automation
Project details
Looking for smart security & automation?
I will develop an AI-powered face recognition system for real-time detection and automation. Perfect for attendance systems, office security, and smart access.
Face detection & recognition in real time
Secure, scalable backend with Python & OpenCV
Integration with apps or IoT devices
Deployment on AWS / GCP / Azure
Protect your business with the power of AI security ️
I will develop an AI-powered face recognition system for real-time detection and automation. Perfect for attendance systems, office security, and smart access.
Face detection & recognition in real time
Secure, scalable backend with Python & OpenCV
Integration with apps or IoT devices
Deployment on AWS / GCP / Azure
Protect your business with the power of AI security ️
AI Development Type
Knowledge RepresentationAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$70
|
Standard
$80
|
Advanced
$100
|
|---|---|---|---|
| Delivery Time | 4 days | 7 days | 12 days |
Number of Revisions | 0 | 1 | 2 |
AI Model Integration | - | ||
Detailed Code Comments | - | ||
Knowledge Graph | - | - | |
Model Documentation | - | - | |
Ontology | - | - | |
Source Code | - | ||
Taxonomy | - | - | - |
About Hemant
AI Backend Engineer | LangGraph, RAG & Multi-Agent Systems (Python)
Pune, India - 9:49 am local time
If your AI system needs to be reliable, deterministic, and scalable, I can help
If you’re exploring AI agents, RAG chatbots, or automation, you’re likely not just looking for code — you want an AI system that behaves predictably, scales safely, and knows when NOT to act.
I’m a Senior Generative AI Engineer with experience building multi-agent systems, RAG pipelines, and AI-powered backend services for enterprise and SaaS products.
What I help clients with:
• Multi-agent AI systems (intent routing, reasoning, guardrails, handoffs)
• RAG-based chatbots using internal documents or databases
• AI agents for incident handling, workflow automation, and decision support
• Python backends (FastAPI / Django) for AI-powered products
• Cloud-ready deployments on AWS
Relevant experience:
• Designed an Agentic Incident Management platform orchestrating multiple AI agents using LangGraph
• Built RAG-based HR and enterprise chatbots reducing query resolution time
• Developed real-time face recognition systems for security and automation
How I usually work:
• Start with a small, clearly scoped prototype
• Validate behavior and edge cases early
• Scale only after the approach proves reliable
If you have an AI idea or automation challenge, feel free to message me — I’ll suggest a practical approach before you commit.
Steps for completing your project
After purchasing the project, send requirements so Hemant can start the project.
Delivery time starts when Hemant receives requirements from you.
Hemant works on your project following the steps below.
Revisions may occur after the delivery date.
Collect requirements and start developing accordingly
Develop and test it thoroughly and get it review iteratively.