You will get safe, AI-powered healthcare assistant for your clinic or healthtech product
Top Rated
Project details
I specialize in healthcare AI, not generic chatbots. I build healthbots that use your real clinical content (via RAG), are designed with safety and “I don’t know” behavior, and fit into your existing workflows. You get a practical, maintainable assistant instead of a fragile demo.
AI Algorithms
Convolutional Neural Network, Large Language Model, Multimodal Large Language Model, Transformer Model, YOLOAI Applications
AI Chatbot, AI Text-to-Image, AI-Enhanced Medical Imaging, Conversational AI, Image AnalysisAI Development Language
PythonAI Tools
PyTorch, TensorFlowAI Models
BERT, ChatGPT, DALL-E, GPT-4, WhisperWhat's included
| Service Tiers |
Starter
$100
|
Standard
$300
|
Advanced
$500
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 28 days |
Number of Revisions | 2 | 3 | 4 |
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 |
2 reviews
(1)
(1)
(0)
(0)
(0)
This project doesn't have any reviews.
DV
DJ V.
Jul 1, 2026
Quality assessment of forensic psychiatric reports using RAG / Langchain
GA
Ghuffran A.
Oct 28, 2025
Build a YouTube Chatbot Using RAG (LangChain + OpenAI)
Amazing experience working with Haider! He built a powerful YouTube chatbot using LangChain and OpenAI with great precision. Highly professional, communicates clearly, and delivers top-quality AI solutions on time
About Haider
AI Voice Agent Developer | Retell/ElevenLabs/LiveKit | AI Agents, LLM
100%
Job Success
Rawalpindi, Pakistan - 11:18 pm local time
I'm an AI Voice Agent Developer with 7+ years of AI engineering experience. Because most of my AI systems needed a real product around them, not just an API, I've also shipped the web, mobile, and desktop apps they run in.
Voice AI Agents:
If your voice agent sounds great in testing and then breaks down on a real call — long pauses, awkward interruptions, or a bill that scales badly with call volume — that's what I fix.
- Self-hosted speech-to-speech pipeline on LiveKit: ~1–1.5 second response latency, low cost, smooth interruption handling, and noise suppression
- Or a managed build on Retell or ElevenLabs if you already have a platform preference — I've delivered the same production use case on all three, so you get the right tradeoff on latency, cost, and control instead of whichever tool I happen to know
AI Agents & LLM Systems:
- Multi-agent orchestration with LangGraph and CrewAI — specialized sub-agents handling distinct steps (planning, execution, verification) instead of one monolithic prompt doing everything
- Built a LangGraph-based AI app-generation system: a multi-step pipeline (spec → plan → scaffold → build → fix → preview) with dedicated tool-agents for file handling, shell commands, and build-error parsing — turning a plain-language request into a working, previewable app with an edit loop for follow-up changes
- Agentic RAG systems built on LLMs (OpenAI, Claude, LLaMA, Qwen) with grounded, citation-backed retrieval over documents and knowledge bases
Computer Vision (GPU & Edge):
- Object detection, segmentation, and multi-object tracking (YOLO, BoT-SORT, Deep SORT)
- Deployment to edge devices (Jetson Nano, Xavier NX) with real-time performance optimization
- Built DentaSmart, a live App Store app that detects and segments dental conditions from X-rays - and oral images, with a patient-facing chatbot for follow-up questions
- Built a real-time pose-correction fitness app that tracks joint angles via mobile camera to detect posture mistakes and correct exercise form live
- Built a drone-based traffic analytics system using fine-tuned YOLO + BoT-SORT for persistent multi-object tracking through occlusion and dense traffic
How I Work:
I don't just deliver a model — I architect and ship the product it lives in: iOS, Android, React/Next.js web apps, Windows desktop applications, and backend (FastAPI/Python), deployed on AWS/GCP. For example, a real-time call-center transcription and supervisor-coaching platform I built runs as a Windows desktop agent app paired with a live web dashboard — two-sided transcripts, AI-assisted reply suggestions, and real-time escalation alerts.
Ideal Clients:
I work best with teams that need to:
✔ Turn an idea into a working AI-powered MVP — one person owning both the AI and the product around it
✔ Replace a fragile AI demo with something production-ready
✔ Add voice AI, AI agents, or computer vision capability to an existing product
✔ Build a multi-agent workflow that actually completes tasks, not just simulates them
✔ Deploy computer vision to real hardware (edge devices, cameras, embedded systems)
Tell me what you're building and where it's currently stuck — I'll give you a straight answer on scope and approach before you spend a connect.
Steps for completing your project
After purchasing the project, send requirements so Haider can start the project.
Delivery time starts when Haider receives requirements from you.
Haider works on your project following the steps below.
Revisions may occur after the delivery date.
Requirements & content
We clarify your goals, target users, main use cases, and collect your FAQs, website text, SOPs, or policies the bot should use.
Design & prototype
I design the bot’s behavior, safety rules, and main flows, then build a first working prototype using your content.