Hi, I'm Usmar.
I build AI you can actually talk to.

AI engineer building voice agents, RAG pipelines, and multi-agent systems that real patients, restaurants, and sales teams use every day. By day I build agents and decision-support systems at Highnoon Pharma; on the side I run Procaply, my captioning product, and teach data visualization and BI at Superior University.

Usmar Haider

Now

Highnoon Pharma 2026 —

🚀 Procaply · 200+ signups

200+ Procaply signups ✦27 caption languages shipped ✦2 university courses taught ✦3.4s voice latency — down from 15s ✦98% intent accuracy in production ✦300+ automated tests on HealthAI ✦2× global hackathon podiums ✦4 speech-to-speech medical specialists ✦3 languages · EN / ES / HI ✦99.9% uptime on live phone lines ✦
Founder · shipped 2026in production

Procaply

My own product: word-by-word video captions in 27 languages for creators, built and run end-to-end — from the speech pipeline to the app store listing.

  • Word-by-word captions — speech-to-text with per-word timing, grouped into caption segments and rendered exactly as the editor shows them — what you see is what gets burned

  • Cross-script translation — an LLM layer romanizes and translates into 27 output languages without touching the timestamps, so Urdu and Hindi creators can caption in Roman script

  • Caption studio — 31 look templates, reveal animations, a bilingual second line, per-word styling, and a brand kit that syncs your fonts, colors, and watermark

  • Production plumbing — background job queue with live progress, accounts with usage quotas, durable project storage, feedback loop, and a native mobile app sharing one API

200+
signups since launch
27
caption languages
3
clients · web, iOS, Android
Open procaply.com
Speech-to-textLLM translationVideo renderingJob queueAuth + quotasNative mobile

procaply · studio · reel_final.mp4

live

00:04.12

Captionsthatlandoneveryword.

ہر لفظ پر کیپشن

word timeline

template bold pop · reveal karaoke

Captions
that
land
on
every
word

1. Upload

any video, any language

2. Transcribe

word-level timestamps

3. Edit

templates, styles, bilingual line

4. Export

captions burned in, ready to post

UrduRoman UrduEnglishHindiPunjabiArabicSpanish+20 more

Background

Education & skills

🎓

MS Artificial Intelligence

LUMS · Lahore · 2026

📊

BS Data Science

FAST NUCES · Lahore · 2024

Certifications

  • Claude Code: A Highly Agentic Coding Assistant — Anthropic, 2025
  • Web Scraping — freeCodeCamp, 2023
  • Joining Data with Pandas — DataCamp, 2022
  • Data Manipulation with Pandas — DataCamp, 2022

AI & agents

LLMsVoice AIRAGMulti-agent systemsMCPFine-tuningGraphRAGNLPComputer vision

Frameworks & models

PyTorchTensorFlowLangChainHuggingFaceFAISSPineconeClaudeBedrockNova Sonic

Data & BI

Data warehousingDimensional modelingETL / ELTOLAPData visualizationDashboardsPandasSQL

Backend & infra

FastAPIWebSocketsAWSDynamoDBMongoDBPostgreSQLDockerCI/CDTwilio

Experience

Where I've shipped

2022 — Present

Jun 2026 — Present

Lahore · On-site

AI & Data Science Engineer · Highnoon Pharma

Bringing agents, decision support, and automation to one of Pakistan’s largest pharmaceutical companies.

LLM agentsDecision supportAutomationData analysisPythonSQL
  • Building LLM agents over internal company data so teams can query information and trigger workflows in natural language
  • Designing an AI decision-support system that turns operational data into recommendations for business teams
  • Automating recurring reporting and document workflows end-to-end, cutting manual hand-offs between departments
  • Leading data analysis across business functions to surface the trends that inform leadership decisions

Jun 2025 — Jun 2026

USA · Remote

Full Stack AI Engineer · DFX5

Built HealthAI, a multi-tenant speech-to-speech healthcare consultation platform used by real clinics.

Amazon Nova SonicBedrockClaudeMCPFastAPIWebSocketsReactAWS
  • Built a real-time speech-to-speech healthcare consultation platform using Amazon Nova Sonic, Bedrock, and Claude 3.5 Sonnet
  • Designed a multi-agent architecture with 4 healthcare specialists (nurse intake, cardiology, neurology, functional medicine) using MCP tools for comprehensive medical support
  • Developed the FastAPI backend with WebSocket streaming, JWT/Cognito auth, and a React/Vite frontend with push-to-talk UI
  • Shipped AI-generated SOAP notes, prescription drafting with doctor sign-off, and a Clinical Intelligence Engine that turns intake, documents, labs, and vitals into clinical briefs
  • Hardened the platform for HIPAA: tenant isolation at the database layer, PHI encryption, audit logging, and 300+ automated tests across backend, frontend, and e2e

Sep 2023 — Jun 2025

Remote

Senior AI Engineer · Eye4Tech

Led RAG and conversational AI work across psychology, sales, and WhatsApp commerce products.

RAGFAISSPineconeAWS S3FastAPIMongoDBTwilio
  • Built the HAI chatbot for Humanop Quantum Psychology: a RAG-into-RAG system on FAISS generating personalized wellness plans from user assessments, with admin feedback folded back into retrieval
  • Deployed FAISS vector databases on AWS S3 with automatic re-embedding on new data, plus multi-file search returning similarity scores and source attribution
  • Developed a sales AI chatbot that classifies queries as general or data-related, routing data queries through ML retrieval and general ones through an S3 knowledge base — multi-vendor with real-time updates
  • Integrated a WhatsApp RAG chatbot over Twilio with a Pinecone pipeline and MongoDB-backed per-user conversation history

2024

Healthcare · Contract

AI Engineer — Client Project · VitalsVault

Voice-based medical assistant with fine-tuned medical LLMs.

MedGemmaGraphRAGLLM fine-tuningVoice AI
  • Cut voice response latency from 15s to ~3.4s by rebuilding the streaming pipeline — a 75% improvement
  • Fine-tuned MedGemma 4B and 27B models for accurate medical knowledge responses
  • Implemented GraphRAG over structured healthcare datasets and automated SOAP note generation with secure email delivery

Sep 2022 — Mar 2023

USA · Remote

Junior Data Analyst · BornGreat

Social media intelligence: scraping, competitor analysis, and sentiment tracking.

PythonNLPWeb scrapingSentiment analysis
  • Extracted and analyzed data from Instagram, Facebook, Reddit, and Twitter for real-time market insight
  • Ran competitor analysis surfacing strengths, weaknesses, and performance gaps
  • Applied NLP and sentiment analysis to track consumer opinion, sharpening campaigns and engagement

Teaching

Visiting Lecturer, Superior University

Teaching final-year data students in Lahore since September 2026

📈

7th semester

Data Visualization

How to turn a dataset into a chart that a decision-maker trusts — visual perception, chart grammar, dashboards, and the honest presentation of uncertainty.

Visual encodingChart grammarDashboardsStorytelling with dataPython & BI tools
🏛️

8th semester

Data Warehouse & Business Intelligence

From operational databases to analytics-ready warehouses — dimensional modeling, ETL/ELT pipelines, OLAP, and the BI layer that sits on top.

Star & snowflake schemasETL / ELTOLAP cubesSlowly changing dimensionsBI reporting

Why I teach: the same warehouse and visualization fundamentals show up every week in the decision-support systems I build at work — teaching them keeps the basics sharp.

Superior University · Lahore · 2 courses · 7th & 8th semester

Voice agents

AI agents that answer the phone

All live in production, talking to real customers

🏥

Healthcare

Hospital appointment agent

Patients call, speak naturally, and leave with a booked appointment. Checks live physician availability, refuses impossible slots, emails confirmations, and cancels via secure verification codes.

98%
intent accuracy
<2s
response time
99.9%
uptime
Voice-to-voiceWebSocketsGPTEmail automation
🍕

Restaurant

Cheezious ordering agent

A voice line that takes complete food orders: navigates the full menu, handles “extra cheese, no onions” requests, recommends dishes, processes delivery details, and reports live order status.

96%
order accuracy
90s
avg. order time
4.8/5
satisfaction
Voice AIMultilingualOrder pipelineTwilio
🩺

Clinical · DFX5

HealthAI consultation agents

Four speech-to-speech specialists — nurse intake, cardiology, neurology, functional medicine — on Amazon Nova Sonic in English, Spanish, and Hindi, with smart triage, red-flag overrides, and outbound calling.

4
specialist agents
3
languages
300+
automated tests
Nova SonicMCP toolsAmazon ConnectMulti-tenant

Awards

Hackathon wins

Two global podiums, one national — with the receipts

Usmar holding the $2,000 second-place check at the Transcend AI Hackathon
🏆 2nd place$2,000 prize

FARM.AI — Transcend AI Hackathon

Pakistan-wide · NETSOL Technologies

AI agriculture assistant: AlexNet trained on 36 plant disease labels, live weather and vegetable-price agents, a personalized agri-doctor, and a multilingual chatbot for farmers.

lablab.ai certificate for second best solution at /execute: AI Genesis
🏆 2nd placeGlobal final

HealthSync.AI — /execute: AI Genesis Hackathon

Global · Dubai, 2025 · lablab.ai

Multi-agent medical assistant: Mistral 7B fine-tuned to read blood reports, plus agents for hospital location, appointment booking, and image-based skin disease detection.

Traversaal × Optimized AI hackathon award certificate for team NGRAM
🏆 Honorable mentionSolo team

Blood.AI — Traversaal × Optimized AI Hackathon

Global · 2025 · Team NGRAM

Blood-health assistant: ML models for blood disease prediction and blood-type classification, a scraping-and-embedding pipeline for contextual Q&A, and agents that find nearby hospitals and donors.

Personal AI stack

The assistant that runs my life

OpenClaw × Hermes Agent — self-hosted, always on, reachable from WhatsApp

OpenClaw logo

OpenClaw

Self-hosted assistant gateway

The open-source gateway that puts my assistant on the channels I already use. It runs on my own hardware — WhatsApp in front, with email, OneDrive, and calendar wired in behind it — so nothing about my inbox or schedule leaves machines I control.

  • An email lands → the agent triages it and pings me on WhatsApp with context and a suggested action
  • I answer in one line; it reschedules the event, updates the calendar invite, and sends the reply itself
  • Email, OneDrive, and calendar integrations with scoped, auditable permissions — self-hosted end to end
24/7
always on, self-hosted
4
integrations — WhatsApp, email, OneDrive, calendar
<1min
email lands → WhatsApp ping
WhatsApp channelEmailOneDriveCalendarSelf-hosted
Gmail
Search mail

1 of 2,143

Can we move tomorrow's 11 AM call?

Inbox
S

Sarah Malik <s.malik@acmehealth.com>

to me ▾

10:41 AM (2 min ago)

Hi Usmar,

Something urgent came up tomorrow morning — could we move our 11 AM call to later in the day? Sorry for the short notice!

Best, Sarah

Reply Forward
OpenClaw gateway → Hermes agent

10:43

🦞

Personal Assistant

+92 310 2277147

online

⋮
Today

🔒 Messages and calls are end-to-end encrypted. No one outside of this chat, not even WhatsApp, can read or listen to them.

📧 New email — Sarah Malik (Acme Health)
"Can we move tomorrow's 11 AM call?"
She has a conflict. Your 3–4 PM is free — want me to reschedule and reply?

10:42

Yes — move it to 3 PM and let her know 👍

10:43 ✓✓

✅ Done — call moved to 3:00 PM tomorrow
· Calendar invite updated, no conflicts
· Polite reply sent to Sarah
· Reminder set 15 min before

10:43

Message

Hermes Agent logo

Hermes Agent

Self-improving agent runtime · Nous Research

The brain behind the gateway. Hermes has a built-in learning loop: every non-trivial task it completes becomes a skill document — the approach, the dead ends, the edge cases — so it handles the same job better next time, and genuinely learns my routines.

  • Writes and reuses skills from experience instead of reasoning from scratch every time
  • Persistent memory across sessions — it builds a deepening model of my preferences
  • Searches its own past conversations to ground new answers in what it already knows
12+
skills written from tasks
41×
top skill reused
100%
memory kept across sessions
Skill learningPersistent memoryAutonomous tasksOpen source

Hermes Agent

Running

Activity

Skills

Memory

Settings

Reschedule call with Sarah (Acme Health)

From email · finished at 10:43 AM

Completed

Read the email and understood the request

10:41

Found a free slot tomorrow — 3:00 to 4:00 PM

10:42

Asked Usmar on WhatsApp, got the go-ahead

10:43

Moved the calendar event · 11:00 → 15:00

10:43

Sent a polite reply to Sarah

10:43

Learned a new skill from this task

"Reschedule a meeting" — saved with the approach and edge cases, so next time takes seconds.

Reschedule a meeting

New · saved just now

Triage the inbox

Used 41 times

Weekly summary

Used 12 times

U

Remembers: prefers afternoon calls · never book Fridays · Sarah = Acme Health lead

What it does for me, unattended

📧

Email autopilot

Triages the inbox, drafts and sends replies on my behalf, and pings me on WhatsApp when something actually needs my attention.

🗓️

Scheduling over WhatsApp

Creates, reschedules, and cancels calendar events from a chat message — with conflict checks and a confirmation before anything is booked.

📁

OneDrive context

Grounded access to my files, so drafts and plans reference the real documents instead of guessing.

🧠

Learns as it goes

Every task it completes sharpens the next one — the assistant I have today is measurably better than the one I set up.

Projects

More work

📞

Real-time healthcare appointment system

Voice-enabled booking over phone calls: WebSocket streaming, live physician availability checks, automated confirmation emails, and health guidance tools for the agent.

WebSocketsGPTVoice AISQL
🧠

Automated student summary evaluation

Combined ADHD and neurotypical student writing into one dataset, then used BERT and DeBERTa to classify summaries and generate actionable feedback. FAST Lahore, 2023–24.

BERTDeBERTaNLPPyTorch
🤟

Hand sign detection

Real-time sign-language-to-text translation from a live camera feed — computer vision for accessible, non-verbal communication.

Computer visionOpenCVTensorFlow
⚙️

MLOps — customer satisfaction

End-to-end ML pipeline with automated deployment, monitoring, and CI/CD — production workflow discipline applied to a customer satisfaction model.

MLOpsCI/CDDockerZenML