Enterprise AI Architect

AI systems that finally match the ambition.

I'm Ahmad Naeem. I build the AI agents, RAG pipelines, and conversational AI that ambitious companies run on. Every system I ship has one condition: it has to work in production, not just in a demo.

125+Projects delivered
100%Job Success Score
10+Products built
Ahmad Naeem, Enterprise AI Architect
Top Rated Pluson Upwork
100%Job Success
AI Agents RAG · Voice AI
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Industries I build for

By the numbers
125+ Projects delivered Enterprise-grade, across 8 industries
27 Upwork contracts Top Rated Plus, 100% Job Success
10+ Products built From AI job radars to payroll platforms
Hello, I'm

Ahmad Naeem.

I build the systems ambition runs on.

I started selling at 17. Back then I didn't know what I was really learning. I thought it was business. It wasn't. It was people.

What keeps a founder up at 2am. What a CEO is afraid to admit in a board meeting. What an operations manager feels when their team is drowning in work that should have been automated two years ago.

A CS degree and a decade later, I stopped consulting on AI and started building it. Because I got tired of watching good businesses move slowly, not from lack of ambition, but from lack of the right system.

In production. Not in demos.

That's what I build now: systems that finally match the ambition. Autonomous agents that eliminate manual decision-making. Knowledge bases you can question in plain English. Support that never clocks out.

Across healthcare, fintech, real estate, legal, e-commerce, SaaS, education, and logistics, I build:

  • AI agents that eliminate manual decision-making at scale
  • RAG systems that make your entire knowledge base instantly queryable
  • Conversational AI across web, WhatsApp, CRM, and voice, always on
  • AI integrated into your existing systems, no rip and replace
Founder proof

I don't just build for clients. I build companies.

Not products I helped with. Companies and brands I founded and run, three of them, live, at real scale.

One engineer. A whole product line.

Beyond the companies, a shelf of standalone products I designed, engineered, and run. Each one started as a real operational problem inside a working business, and each one has intelligence planned into the architecture, not bolted on. All shipped. All in production today.

01

Marvel: never miss a job worth winning

AI Job Radar · In production

Finding the right work on Upwork means refreshing all day and arguing over which jobs deserve a proposal. Good opportunities get seen a day too late, and connects get spent on jobs you would never win.

Marvel watches Upwork around the clock, runs hard rules before any AI spend, then scores every surviving job 0 to 100 for fit with the reason written out. The board opens each morning already sorted by what is worth winning.

24/7always scanning
0-100AI fit score, with reason
AI job scoringHard rules firstLive discovery
Explore Marvel
02

Ultron: from a blank page to a winning proposal

AI Proposal Engine · In production

Great proposals win jobs, but writing a tailored one for every opportunity is slow, and generic templates lose. Most teams either burn hours or send weaker work.

Ultron drafts a tailored, on-brand proposal in seconds using retrieval over the real portfolio, then lets you refine it. RAG, applied to selling.

Secondsfrom job to draft
Your voicelearned from wins
LLM + RAG corePortfolio retrievalTone control
Explore Ultron
03

Pulse: turn a team’s effort into one number you can trust

Performance Intelligence · In production

Activity is easy to see but hard to compare. One person makes more calls, another closes more, and 'who is actually performing' becomes an argument instead of a fact.

Pulse weights every KPI into a single, fair score, ranks the team on a live leaderboard, and flags who is drifting before a manager has to notice.

One scoreweighted from every KPI
Liveleaderboard & funnel
AI performance flagsWeighted scoringLive leaderboards
Explore Pulse
04

Attendly: attendance that fits how you really work

Workforce Attendance · In production

Most attendance tools assume a nine-to-five. They break the moment a shift crosses midnight, punish someone for a schedule that isn't their fault, and still need a spreadsheet.

Attendly understands night shifts, breaks, and overnight work, tracks status automatically, and gives managers a live picture of who is on right now.

Overnightshifts across midnight
Autostatus & check-out
Smart status engineAbsence flagsAuto reports
Explore Attendly
05

Vault: payroll and payslips, without the paperwork

Payroll & Compensation · In production

Pay is the most sensitive thing a team touches, and the easiest to get wrong in a spreadsheet. One stale formula, one shared file, and trust is gone.

Vault computes every salary, bonus, and payslip by rule, sweeps the run with an audit pass that catches outliers, and keeps bank details behind a second lock.

Every cyclepayslips generated
Privatebank details secured
AI audit passCommission engineExtra-locked access
Explore Vault
06

Loop: the whole team’s conversations, in one place

Team Communication · In production

Context lives where the work lives, but the conversation usually lives in a separate chat app nobody keeps open, where decisions quietly get lost.

Loop puts real-time messaging right inside the platform, next to the deal it is about, and keeps the history searchable as team knowledge.

Real-timemessaging built in
Mobile-firstgreat on any phone
AI-searchable historyChannels & DMsIn-context chat
Explore Loop
07

BlackMind: a private AI workspace for the team

Private AI Workspace · In production

A capable AI is table stakes now, but the easy options mean pasting your company's context into someone else's tool, with no idea where it ends up.

BlackMind gives the team a strong AI for research and drafting, grounded on the live web and able to read images, without work leaving the workspace.

Live webgrounded, current answers
Privateinside your workspace
LLM workspaceWeb research modePrivate by design
Explore BlackMind
Selected work

Real systems. Real numbers. In production.

Three engagements, told the way they happened: the problem, the system, and what changed.

01

From 4 hours to 8 minutes: autonomous document processing

AI Architect & Lead Developer

A fintech company had a team manually processing hundreds of documents every single day. Extracting data, categorizing, routing, verifying. Good people doing work that was slowly breaking them.

We built an autonomous AI agent that handles the entire workflow. Processing time dropped from 4 hours to 8 minutes. Human error hit zero. The team was freed to do work that actually mattered.

8 minfull daily workflow
0human errors
AI Agent DevelopmentLangChainFastAPIAutomation
02

24/7 AI support agent: zero added headcount

AI Architect & Lead Developer

An e-commerce brand was losing customers every night. Their support team clocked out at 6pm. Questions went unanswered. Carts abandoned. Customers left.

We built a conversational AI agent that never sleeps. It handles inquiries, processes returns, escalates when needed. Response time dropped from hours to seconds. Support costs cut by 60%.

60%support costs cut
Secondsresponse time, from hours
Conversational AIAI Agent DevelopmentOpenAI APILangChainChatbot Development
03

Enterprise RAG system: ask your documents anything

AI Architect & Lead Developer

A legal firm was drowning in contracts. Thousands of documents, no way to search them meaningfully. Staff spending hours finding answers that should have taken seconds.

We built a RAG pipeline that changed everything. Now their team types a question in plain English and gets the exact answer, source cited, in under 30 seconds.

1000sof documents indexed
<30sto a cited answer
Retrieval Augmented GenerationPineconeOpenAI APILangChainFastAPI
How I work

From wasted hours to working systems.

01

Find the waste

I sit inside your operations and find exactly where human time is being burned on work a system should be doing.

02

Design the system

Agents, retrieval, integrations: the architecture that fits how you already work. Most business problems aren't technology problems. They're workflow problems.

03

Ship to production

Not a proof of concept. A deployed system handling real volume, wired into your stack, with humans in the loop where they belong.

04

Prove it with numbers

4 hours to 8 minutes. Costs cut 60%. Answers in seconds. If the numbers don't move, the system isn't finished.

Capabilities

The skills under every system.

A decade across sales, engineering, and AI, compressed into the capabilities that actually ship product.

AI Engineering

  • AI agents & multi-agent systems (CrewAI, AutoGen)
  • RAG architecture & retrieval tuning
  • LLM orchestration with LangChain
  • Prompt engineering & evaluation
  • Conversational & voice AI design
  • Embeddings, vector search, reranking

Platform Engineering

  • Python & FastAPI back ends
  • APIs: REST, GraphQL, webhooks
  • PostgreSQL, Supabase, SQLite
  • Vector stores: Pinecone, Weaviate, FAISS
  • Docker, AWS, Nginx, Linux servers
  • Auth, roles & security hardening

Automation & Integration

  • Workflow automation with n8n & Make
  • CRM, WhatsApp & voice channel integration
  • Data pipelines & document processing
  • Legacy system integration, no rip and replace
  • Push notifications & real-time UX
  • Production monitoring & health alerts
The stack I build on

Chosen per problem. Not per hype cycle.

Models
OpenAIClaudeLlama 3
Orchestration
LangChainCrewAIAutoGen
Retrieval
PineconeWeaviateFAISS
AI Practice
Prompt engineeringEvalsEmbeddingsFine-tuning
Backend
PythonFastAPINode.js
Frontend
JavaScriptProgressive Web AppsReal-time UI
Data
PostgreSQLSupabaseSQLite
Infrastructure
AWSDockerNginxLinux
Automation
n8nMakeWebhooksCron pipelines
Speech & Voice
WhisperText-to-speechTelephony APIs
Channels
WebWhatsAppVoiceCRM
The road here

A decade of shipping.

Apr 2024
Jan 2026

AI Consultant & Engineer Urban BJK

Working with SMBs and enterprises across healthcare, fintech, real estate, and legal to design and deliver AI systems that change how they operate. Autonomous agents that eliminated manual decision-making, RAG pipelines that turned thousands of documents into instant answers, and voice systems that handle customer calls around the clock. Every project taken on with one condition: it has to work in production, not just in a demo.

Feb 2022
Apr 2024

AI Integration Specialist Innovatek Global

Helped 15+ businesses take their first step into AI. Not by selling them software, but by sitting inside their operations and finding exactly where human time was being wasted. Automated repetitive workflows, built intelligent APIs, and deployed first conversational systems. Most clients had never touched AI before. By the end, they couldn't imagine working without it.

Before
that

AI Workflow Automation n8n & Make

Before building complex AI systems, the work starts somewhere simpler: making things connect. Years spent automating business workflows, integrating CRMs, APIs, and data sources into systems that run without human intervention. This is where I learned that most business problems aren't technology problems. They're workflow problems. AI just makes the solution permanent.

Credentials

The paper behind the practice.

Education

Master of Science in Computer Science University of West Georgia 2024 to 2026
Bachelor's Degree, Computer Science Times University, Multan 2020 to 2024

Certifications

Generative AI with Large Language Models Coursera Issued March 2026
Building Systems with the ChatGPT API DeepLearning.AI Issued February 2026
LangChain for LLM Application Development DeepLearning.AI Issued January 2026
If I take on your project, I already know I can deliver it. And if I'm ever wrong about that... full refund. No questions asked.
My commitment, on every engagement

Working on something serious?

Tell me where your team's time is going, and I'll show you the system that gets it back. AI agents, RAG, conversational and voice AI, built to run in production from day one.

Top Rated Plus. 100% Job Success Score. Upwork is the one channel I take new projects through.