AI That Ships
and Stays Running
Most businesses already know where AI can help, the problem is getting it to actually work in production. I build the systems that close that gap: voice agents, RAG pipelines, workflow automation, and custom LLM tools that run reliably from day one.
Humayun Hasan
AI Automation Expert
Industries Served
Most businesses don't have an AI problem — they have an implementation problem.
The use cases are obvious, such as automate workflows, handle calls, process documents. But prototypes don't ship, integrations break, and nothing runs in production. That's the gap I close.
I work with agencies, clinics, law firms, e-commerce operations, and other businesses that need AI to actually function inside their workflows, not sit in a demo environment. Voice agents that handle real calls, RAG systems connected to live business data, document pipelines that eliminate manual entry, automation that runs without someone babysitting it.
I've worked across enough industries to know exactly what breaks and why. Whatever the use case, I build it production ready from day one.
What I Build
“Whatever the use case, I build it production ready from day one. Not a prototype. Not an experiment. A system your team can rely on.”
Six Ways AI Can Move Your Business
Every engagement starts with a real business problem, not a technology preference. Here's what I build, and what each system is designed to deliver.
AI Workflow Automation
Invoices, support tickets, lead research, email drafting, all automated end-to-end and connected to your existing tools. No more manual handoffs, no more repetitive tasks eating your team's time.
Voice AI Systems
Full voice pipeline builds, such as Deepgram or Whisper for STT, GPT-4o or Claude for conversation logic, ElevenLabs for natural TTS. Low latency, production hardened, and integrated with your calendar, CRM, and backend.
RAG Systems & Knowledge AI
Connecting AI to your private data, such as documents, Notion, Google Drive, SQL databases, internal wikis. Accurate, grounded responses drawn directly from your knowledge base, not hallucinated.
Custom LLM Agents
Autonomous agents that coordinate multi-step workflows, use tools, process data, and take action independently. Built with LangGraph or CrewAI for complex reasoning flows that go beyond a single model call.
AI Strategy & Implementation
Figuring out where AI creates real ROI before writing a single line of code. I audit your workflows, identify high-value automation opportunities, and map a practical implementation path that actually ships.
Computer Vision & ML
Object detection, defect inspection, classification, and custom ML pipelines, from cloud deployment to FPGA edge devices. Built for retail quality control, manufacturing inspection, and medical imaging use cases.
17 Systems Built for Real Business Outcomes
Each project started with a genuine operational problem. Click any card to read the full case study.
Voice AI Systems
AI Voice Receptionist
Twilio · GPT-4o · ElevenLabs
A service business was losing leads simply because no one picked up the phone. They needed a system that handled inbound calls professionally, qualified callers, and booked appointments, without any human involvement.
AI Workflow Automation
HubSpot AI Lead Qualifier
OpenAI · Twilio · HubSpot
This client needed a system that could handle the entire lead qualification process automatically, across both chat and voice, without a human touching it until the lead was actually ready to close.
AI Workflow Automation
AI Lead Gen Pipeline
OpenAI · Playwright · SendGrid
Finding leads manually is slow, inconsistent, and doesn't scale. This client needed a system that could identify prospects, research them, write personalized outreach, and send it all without a human in the loop.
AI Workflow Automation
AI Workflow: Capture, Decide, Act
n8n · OpenAI · HubSpot
Most businesses have tools that don't talk to each other. Leads come in from one place, someone manually checks them, someone else updates the CRM, and half the follow-ups never happen. This client needed all of that to run on its own.
RAG Systems & Knowledge AI
AI Invoice & Document Processing
GPT-4o · OCR · FastAPI
Businesses dealing with high document volumes, such as invoices, contracts, and forms that were spending hours on work, which should take seconds. Manual data entry was slow, error-prone, and completely unnecessary.
Custom LLM Agents
Multi-Agent Research Pipeline
CrewAI · LangChain · GPT-4o
Research that used to take a team days, such as competitor analysis, market trends and product positioning. These were being done manually, inconsistently, and eating time that could be spent acting on the insights.
Computer Vision & ML
LungPulse
Pneumonia Detection · Deep Learning
A hospital network faced critical delays in reviewing chest X-rays during peak flu and RSV seasons, creating dangerous backlogs in pneumonia diagnosis and patient triage.
Computer Vision & ML
Frutect
Fruit Defect Detection · YOLOv8
A regional agricultural distributor faced delays and inconsistencies in manually sorting thousands of units of produce daily. It was an error-prone process leading to downstream quality complaints and unnecessary food waste.
RAG Systems & Knowledge AI
SnapStore AI Support
Bilingual RAG · FAISS · LangChain
A fast growing premium e-commerce brand was overwhelmed by rising support volume in two languages. They needed an intelligent system that could handle complex product queries in English and Spanish without compromising user experience.
AI Strategy & Implementation
Dashflow
AI Analytics Dashboard Builder
Startups, agencies, and e-commerce brands were wasting hours compiling reports from scattered data sources. They needed a single view of their business performance without a full BI team.
AI Strategy & Implementation
Tutoric
AI Tutoring Platform · EdTech SaaS
Students were spending hours manually creating study materials from lecture notes and PDFs. They needed a faster way to turn raw learning content into structured, exam-ready resources.
RAG Systems & Knowledge AI
LegalAlly
AI Contract Review · Legal SaaS
Law firms, agencies, and businesses were spending significant time reviewing contracts and legal clauses manually, which was slow, expensive, and inconsistent across reviewers.
RAG Systems & Knowledge AI
AI Support Agent on Your Docs
RAG · Pinecone · GPT-4o
A business was drowning in repetitive support tickets, answering the same questions manually every day.
Custom LLM Agents
Autonomous Research Agent
LangChain · GPT-4o
A marketing team was spending days manually researching competitors and market trends with inconsistent and outdated results.
RAG Systems & Knowledge AI
SaaS Product Support Agent
RAG · Pinecone · GPT-4o
A SaaS business was losing potential customers because support couldn't answer product questions fast enough.
Voice AI Systems
Voice Agent Call Flow Fix
Voice AI · Calendar Integration
A voice AI agent was capturing customer details incorrectly, double-booking appointments, and giving irrelevant responses mid-call.
RAG Systems & Knowledge AI
RAG Chatbot Accuracy Fix
Vector DB · Embeddings · RAG
A RAG chatbot was generating incorrect answers, failing to retrieve relevant documents, and responding too slowly for real use.
The Stack I Work With Every Day
Not a list for show. These are the tools I actually ship with. These are chosen because they are production tested and genuinely reliable.
Cloud & Deployment
Agent Frameworks
Automation
Vector & Retrieval
Voice AI
Vision & ML
Backend & APIs
Frontend
And more...The right tool is always chosen for the specific problem, not habit.
From Business Problem to Running System
Every system I build starts with a genuine understanding of the problem, not a technology demo looking for a use case.
Problem-first, not technology-first
Production readiness is never optional
Integration into your actual workflows
Iterate until it genuinely works
Understand the Workflow
Before selecting any technology, I map the actual business workflow, where the friction is, what the real bottleneck costs, and what a successful outcome looks like for your team. Most failed AI projects skipped this step.
Design a Practical Solution
With the problem clearly defined, I architect the right solution, not over-engineered, not under-built. I pick the right AI stack, integration layer, and data flow for your specific use case, not the flashiest one.
Build and Integrate
I develop with production in mind from the first commit. Clean APIs, proper error handling, real data, real edge cases. Integration into your existing tools is a first-class concern, not an afterthought bolted on at the end.
Refine Until It Works
AI systems need tuning beyond the initial build. I iterate on response quality, latency, edge cases, and system reliability until the solution is ready to run in production, while being unattended and dependable.
I Don't Hand Off a Build and Disappear
Once a system goes live, I stay close, catching edge cases, handling integrations that shift, and making sure what I built keeps working the way it should. Most clients come back not because the first project failed, but because it worked and they want more of it.
Delivered on Time, Integrated Cleanly
Systems that ship on schedule, documented so your team can actually use them, not just admire them. Every build comes with clear handoff documentation and integration guides.
Real Operational Impact
Reduced processing time, fewer manual handoffs, workflows that run without someone babysitting them. The deliverable isn't code, it's the operational change the code enables.
No Surprises, No Ghosting
Clear communication throughout, you always know what's being built, why it's being built that way, and what comes next. If something changes, you hear about it first.
AI becomes valuable only when it survives real workflows.
— Humayun Hasan
Voice AI
Voice AI that handles real inbound calls end-to-end
RAG System
RAG assistant that freed a support team from repetitive queries
LLM Agent
Lead research agent that moved a sales team from prospecting to closing
Automation
Invoice pipeline that eliminated manual data entry completely
Built for Businesses
Done with Prototypes
If you know where AI should help but can't get it to run reliably in production, that's the problem I solve. Voice agents, RAG systems, workflow automation, and custom LLM tools, built to actually work.
The work speaks for itself.