You will get an AI Observability and Monitoring Setup (Langfuse, LangSmith, Custom)
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Project details
Your AI app is live but you're flying blind. You don't know which prompts are failing, how much each request costs, whether quality is degrading, or why the agent loops sometimes.
I set up LLM observability so you can see exactly what's happening inside your AI system. every trace, every token, every decision, every cost.
What I set up:
• end-to-end tracing for every LLM call, RAG retrieval, and agent step
• cost dashboard: spend per model, per user, per feature
• latency monitoring: P50, P95, P99 response times
• quality evaluation: automated scoring for hallucination, relevance, and accuracy
• prompt versioning: track which prompt version performs best
• alerting: get notified when costs spike, quality drops, or errors surge
• session replay: debug failed conversations step by step
I work with Langfuse (open source, self-hosted), LangSmith, Helicone, or custom dashboards, depending on your stack and data requirements.
If your AI app is in production and you can't answer "what went wrong with that request" in under 60 seconds, you need this.
I set up LLM observability so you can see exactly what's happening inside your AI system. every trace, every token, every decision, every cost.
What I set up:
• end-to-end tracing for every LLM call, RAG retrieval, and agent step
• cost dashboard: spend per model, per user, per feature
• latency monitoring: P50, P95, P99 response times
• quality evaluation: automated scoring for hallucination, relevance, and accuracy
• prompt versioning: track which prompt version performs best
• alerting: get notified when costs spike, quality drops, or errors surge
• session replay: debug failed conversations step by step
I work with Langfuse (open source, self-hosted), LangSmith, Helicone, or custom dashboards, depending on your stack and data requirements.
If your AI app is in production and you can't answer "what went wrong with that request" in under 60 seconds, you need this.
AI Algorithms
Large Language Model, Transformer ModelAI Applications
AI Chatbot, AIOps, Conversational AIAI Development Language
PythonAI Tools
Azure OpenAIAI Models
ChatGPT, GPT-4What's included
| Service Tiers |
Starter
$500
|
Standard
$1,500
|
Advanced
$3,500
|
|---|---|---|---|
| Delivery Time | 5 days | 14 days | 28 days |
Number of Revisions | 0 | 0 | 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 |
Frequently asked questions
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NF
Nicholas F.
Apr 3, 2026
Continuous AI Development
Really, really liked working with Hassan. His team is very professional.
AA
Asma A.
Mar 24, 2026
Looking for a Next JS Team for Staff Augmentation
Hassan is very approachable and a pleasure to collaborate with!
RD
Ronnie D.
Feb 10, 2026
Help Chatbot Prompt Engineering & RAG + Formatted Responses
Hassan and team were great and got my 1st version of the product up and running very successfully.
PP
Paul P.
Jan 4, 2026
Build SaaS on Supabase and Lovable
AB
Adnan B.
Dec 9, 2025
60 minute consultation
About Hassan
AI Automation & SaaS | Claude Partner | Lovable + Supabase | 27+ Apps
100%
Job Success
Peshawar, Pakistan - 4:10 am local time
I build AI agents, SaaS platforms, and automation systems. I have been writing code professionally since 2015 and shipped deep learning systems before ChatGPT existed.
Background: MSc in Electrical Engineering (University Gold Medalist). Published researcher in deep learning and computer vision. Ex-Pakistan Air Force R&D engineer on satellite image recognition. Former CTO at Atarim, a UK SaaS company, for 4 years. 43 machine learning projects delivered on Fiverr before moving to Upwork full time. AI consultant to Pensa Systems (Austin, TX), building multi-agent LLM systems with LangGraph and RAG on AWS EKS.
Today I run Tech Emulsion, a 30-person engineering team and official Anthropic partner agency. You still talk to me. I join every call, I make the software architecture decisions, and I will tell you when something is a bad idea before you spend money on it. Behind me: engineers, QA, DevOps, and project management, with code reviews, automated testing (Jest), and CI/CD in every sprint.
RECENT RESULTS:
- Autonomous outbound agent for a San Diego marketing agency. Finds and enriches leads, redesigns each prospect's website as a live demo, and launches approved campaigns into Instantly and GoHighLevel.
- Voice AI for a premium Shopify meat brand. Recovers abandoned carts and texts a discounted checkout link during the call.
- AI content engine for a UK food brand. Writes posts in the founder's voice and rejects off-brand drafts on its own.
- Shopify checkout app with an 11% attach rate across 6,500+ orders.
- Replaced 4 hours a day of manual data entry with zero for one automation client.
WHAT I BUILD:
AI AGENT DEVELOPMENT & CHATBOTS
Custom AI agent and chatbot development, plus Retrieval Augmented Generation (RAG) systems trained on your data. Voice AI agents on Retell, Vapi, and ElevenLabs that answer inbound calls, qualify leads, and book appointments into your CRM. RAG pipelines that turn 200-page manuals into instant answers. A GPT chatbot tied into Shopify that handled 80% of support questions without a human. Generative AI, large language model integration, prompt engineering, and natural language processing across the stack.
AI CONSULTING & CLAUDE IMPLEMENTATION
I am an official Anthropic partner. I work across the Claude stack: Claude API, Claude Code, Agent SDK, MCP servers, and Cowork. I help you find where AI fits, then my team builds it: document processing, report generation, code review, data extraction, content pipelines, internal knowledge bases. If a process eats 20+ hours a week, I scope the AI implementation, design it, and we ship it.
WORKFLOW & BUSINESS PROCESS AUTOMATION
Automated workflows that connect your tools so data moves without manual work. Lead routing, follow-ups, CRM logging, document processing, notifications. n8n, Make, Zapier, and custom API integrations end to end.
FULL-STACK SAAS & WEB APPLICATION DEVELOPMENT
Production SaaS from zero to launch in 4 to 8 weeks. Front-end development in Next.js, React, and Tailwind CSS. Back-end development in FastAPI, Node.js, and Django. Database architecture on Supabase and PostgreSQL. Auth, Stripe payments, dashboards, admin panels, REST APIs, microservices, and real-time features with Websockets.
LOVABLE, REPLIT & BOLT RESCUE
Broken prototype from a low-code or no-code AI builder? I fix it inside Lovable or rebuild it on Next.js, Supabase, and FastAPI. Auth failures, broken Supabase connections, missing backend logic, payment issues. I have taken rescues to production in field service management, telecom, and advertising.
MOBILE APP DEVELOPMENT
AI mobile app development with React Native. Nutrition tracking, calorie counting, VPN clients, fitness apps. Full iOS and Android deployment.
CHROME EXTENSIONS & WEB AUTOMATION
Google Chrome extensions for WhatsApp automation, LinkedIn content analysis, and visual feedback tools. Data scraping and web automation systems.
STACK: Next.js, React, React Native, TypeScript, JavaScript, HTML5, CSS, Tailwind CSS, Redux, Material UI, Node.js, ExpressJS, FastAPI, Django, Python, GraphQL, REST API, Supabase, PostgreSQL, MongoDB, MySQL, Firebase, Docker, Amazon Web Services (AWS), Git, GitHub, Figma, Stripe, Twilio, Claude API, OpenAI API, ChatGPT API, Gemini, LangChain, LangGraph, Pinecone, ChromaDB, n8n, Make, Zapier, machine learning, deep learning, MLOps.
Certifications: IELTS (English proficiency), React Nanodegree, Machine Learning (Stanford), Deep Learning Specialization (DeepLearning.AI).
Send me a message or invite me to your job. Free 30-minute scoping call before any commitment. You own all code, repos, and accounts.
Steps for completing your project
After purchasing the project, send requirements so Hassan can start the project.
Delivery time starts when Hassan receives requirements from you.
Hassan works on your project following the steps below.
Revisions may occur after the delivery date.
Audit Current Stack
Review your AI app architecture, LLM calls, and existing logging.
Instrument Traces
Add tracing to every LLM call, retrieval step, tool use, and agent action.