Hello! 👋 Welcome to my portfolio

I'm Hardik Agarwal

AI Systems Architect

I design and deploy AI-powered revenue, calling, and automation infrastructure that replaces manual teams and scales businesses.

About Me

I build scalable AI infrastructure systems for revenue, communication, and automation. My work includes high-volume AI call centers handling 10,000+ calls per day, autonomous pre-sales systems, on-premise AI voice deployments, outreach automation engines, and AI-powered content generation systems. I focus on system architecture, scalable backend automation, LLM-driven workflows, voice AI infrastructure, revenue process automation, and open-source contribution & optimization.

Infrastructure & Stack

AI & LLM Systems
Voice AI Infrastructure
Workflow Automation
API Integrations
Backend Orchestration
System Architecture
Open-source Optimization

Systems Built

Production-grade AI infrastructure systems designed for scale

01

AI Call Center Infrastructure (10K+ Calls/Day)

Designed and deployed a scalable AI-powered outbound calling infrastructure capable of handling 10,000+ calls per day with intelligent conversation handling and automated lead qualification. Features high-volume outbound call orchestration, dynamic conversation flow handling, intelligent lead qualification, smart routing & data logging, and scalable backend workflow automation.

LLM APIsVoice AITelephony APIsBackend OrchestrationWorkflow Automation

Impact:Replaced manual outbound teams and significantly reduced operational cost while maintaining high throughput.

02

Autonomous AI Pre-Sales System

Built an AI-driven pre-sales automation system that captures, qualifies, nurtures, and schedules leads without human SDR involvement. Includes real-time lead capture, automated qualification logic, follow-up sequencing, CRM integration, and appointment scheduling.

LLM WorkflowsWebhooksCRM IntegrationsAutomation Engine

Impact:Reduced response time to near zero and improved qualification efficiency.

03

AI UGC Generation Engine

Developed an automated AI content pipeline that generates marketing scripts, voiceovers, and short-form video content at scale. Features AI script generation, automated voice synthesis, batch reel production workflows, and content pipeline automation.

LLM APIsVoice SynthesisMedia Automation Workflows

Impact:Reduced content production time by 70–80%.

04

On-Premise AI Voice Agent Deployment

Deployed privacy-first AI voice agents directly on client infrastructure, enabling secure local processing without cloud dependency. Includes local server deployment, voice processing integration, LLM backend orchestration, and enterprise-grade control.

Self-Hosted AI StackLocal Server InfrastructureVoice ProcessingLLM Backend

Impact:Enabled enterprise-level AI automation with full infrastructure control.

05

AI Travel Booking Chatbot

Built a conversational AI chatbot integrated with travel booking APIs for real-time availability checks, bookings, and automated confirmations. Features conversational booking logic, API integrations, workflow automation, and automated confirmations.

LLM APIsAPI IntegrationsBackend Automation

Impact:Reduced booking friction and automated support workload.

06

Outreach & Automation Engine

Customized and optimized open-source outreach systems for LinkedIn automation and cold outreach workflows. Includes open-source modification, workflow automation, personalization logic, and outreach scaling.

Open-source ToolingAutomation FrameworksWorkflow Engines

Impact:Improved personalization efficiency and automation reliability.

07

Anti-Scam Honeypot Intelligence System

Developed a honeypot system designed to detect scam activity, collect malicious interaction data, and forward structured reports to government reporting channels. Features trap endpoint design, activity logging engine, structured evidence collection, and automated reporting pipeline.

Backend LoggingAutomated Reporting WorkflowsSecurity Logic

Impact:Enabled scam tracking and structured evidence generation.

Open Source Contributions

Contributing to open-source projects and improving automation infrastructure

Listmonk – Email Marketing Infrastructure

Email automation workflows, bug identification, and system improvement suggestions

Details

  • Analyzed campaign and subscriber management flows
  • Identified workflow inefficiencies and usability issues
  • Reported bugs and improvement recommendations
  • Contributed feedback to improve automation reliability

Relevance:Strengthened understanding of large-scale email infrastructure and backend campaign orchestration

Dograh – Platform Improvement & Issue Reporting

Bug reporting, feature refinement discussions, and system optimization feedback

Details

  • Identified functional inconsistencies
  • Documented reproducible issues
  • Suggested platform-level improvements
  • Participated in improving system clarity and structure

Relevance:Hands-on exposure to platform debugging and collaborative improvement processes

OpenOutreach – Workflow Customization & Optimization for LinkedIn

Customized internal workflows and optimized automation logic for outreach scaling

Details

  • Modified outreach workflows for personalization
  • Improved automation reliability
  • Optimized response handling
  • Enhanced scaling logic for internal use

Relevance:Practical experience adapting open-source systems for real-world automation needs

Experience

AI Systems Architect

Independent AI Systems Developer

2023 - Present
  • Designed and deployed production-grade AI automation systems
  • Built high-volume voice AI infrastructure handling 10,000+ calls daily
  • Developed scalable outreach and pre-sales automation engines
  • Implemented self-hosted AI voice deployments for enterprise clients
  • Contributed to and improved open-source tools (Listmonk, Dograh, OpenOutreach)
  • Focus areas: AI infrastructure · Revenue automation · Voice systems · Backend workflows · Open-source optimization

Education

B.Tech in Computer Science

Amity University

2024 - 2028 (Expected)
  • Rajasthan, India
  • Currently building production-grade AI infrastructure systems alongside academic training