DHRUV PATHAK/AHMEDABAD, INDIA
AI SOLUTIONS ENGINEER

I DON'TJUST BUILD AI.

Dhruv Pathak — AI Solutions Engineer
CORE THESIS

“I don't just build AI. I figure out where it belongs.”

AI Solutions Engineer working across AI adoption, solution architecture, automation and business workflows — turning messy operational problems into practical, deployable systems.

I FIGURE OUT WHERE IT BELONGS.
“BRIDGING BUSINESS PROBLEMS & TECHNICAL EXECUTION”
02WHO I AM / POSITIONING

I WORKBETWEENBUSINESSANDTECHNOLOGY.

AI Solutions Engineer with hands-on experience turning business requirements into AI-powered applications, intelligent workflows, automation systems, and deployable solutions.

CORE CAPABILITIES
AI ADOPTIONSOLUTION ARCHITECTUREAI AGENTSAUTOMATIONVOICE AICRM INTEGRATIONTECHNICAL DELIVERY
Discover before designing. Prioritise before building. Measure before scaling.
03METHODOLOGY / HOW I THINK

HOW I THINK.

The technology is rarely the first question.

AI adoption starts with diagnosis, not technology. Installing an LLM over a broken manual workflow produces automated chaos. We identify the bottleneck first.

01

DISCOVER

Understand the business before touching technology.

Every client project begins by understanding revenue models, frontline team realities, current software stacks, and operational constraints.

Deliverable: Process Flowchart
02

DIAGNOSE

Find the bottleneck, not just the symptom.

Clients often ask for 'an AI agent' when their root problem is messy CRM hygiene, unclear qualification rules, or broken handoffs.

Deliverable: Root-Cause Diagnostic Report
03

PRIORITISE

Identify where AI creates real leverage.

Not every process needs machine learning. We evaluate interventions on a strict matrix of technical feasibility versus commercial lift.

Deliverable: AI Opportunity Matrix
04

BUILD

Design the smallest valuable solution.

Avoid bloated multi-month engineering cycles. We architect modular, robust solutions that integrate directly into existing tools.

Deliverable: Production Architecture Blueprint
05

MEASURE

Prove whether the business actually improved.

An AI deployment is a failure if frontline employees ignore it. We monitor adoption metrics, calculate hard ROI, and refine.

Deliverable: Post-Launch Adoption Audit
04DEFENSIBLE OUTCOMES / PROOF

PROOF > PROMISES.

Real deployments. Measured operational impact. No fabricated statistics.

EVIDENCE 01
60%
LESS MANUAL PROSPECTING

Across partnership acquisition pipeline at Clozzet India

EVIDENCE 02
3×
QUALIFIED LEADS / WEEK

Sustained pipeline acceleration via automated outreach & scoring

EVIDENCE 03
15+
INBOUND LEADS CONVERTED

Via deployed production Voice AI calling agent

EVIDENCE 04
10 HRS
MANUAL SALES WORK SAVED / WK

Per rep on research, ICP evaluation, and sequence drafting

EVIDENCE 05
500+
ACTIVE ERP USERS

Full lifecycle institutional platform delivery across faculty & admin

EVIDENCE 06
91%
ML PREDICTION ACCURACY

Early intervention risk classification model using Python & Scikit-learn

05SELECTED WORK / ARCHITECTURAL CASE STUDIES

SELECTED WORK.

Four production implementations demonstrating client discovery, architecture, and defensible ROI.

01PRODUCTION VOICE AI
15+ INBOUND LEADS CONVERTED

PRODUCTION VOICE AI CALLING AGENT

Designed and deployed production-grade inbound and outbound Voice AI agents with custom conversational logic, CRM integration and booking workflows for a live admissions advisory client.

Solved after-hours international lead leakage. Sub-2s response latency with live HubSpot CRM lead creation and Google Calendar appointment reservations.
ElevenLabsLangChainREST APIsHubSpot CRMGoogle Calendar
SYSTEM PIPELINE:
01 Telephony Ingestion
02 ElevenLabs Voice Stream
03 LangChain Logic Engine
04 CRM Auto-Sync (#HubSpot)
05 Calendar Confirmation
06 Human Advisor Handoff
READ ARCHITECTURE
02MULTI-AGENT AUTOMATION
10–15 LEADS/WK · ~10 HRS SAVED/WK

MULTI-AGENT AI BUSINESS AUTOMATION

Sales teams spend hours researching target accounts, assessing ICP fit, and writing outreach. Deployed an autonomous agentic pipeline qualifying prospects and generating bespoke outbound sequences.

MINIMAL ARCHITECTURE FLOW:
ACCOUNT→RESEARCH→QUALIFICATION→OUTREACH→CRM
LangChainLangGraphLLM Orchestrationn8nApollo.ioHubSpotPython
VERIFIED IMPACT:
  • • 10–15 target accounts autonomously qualified per week
  • • ~10 hours saved per sales rep every week
  • • Deterministic ICP scoring threshold preventing low-value clutter
READ ARCHITECTURE
03REVOPS & ACQUISITION
60% LESS EFFORT · 3× LEADS/WK

AI-POWERED PARTNER ACQUISITION

Engineered automated acquisition workflows combining AI agents, CRM pipeline logic, and multi-channel outreach for India's first hyperlocal fashion marketplace (Clozzet India).

CORE FORMULA: AI AGENTS + CRM + AUTOMATION
n8nMakeHubSpot CRMApollo.ioWhatsApp Business API
OPERATIONAL RESULT:
  • • 60% reduction in manual prospecting effort
  • • 3× qualified brand leads generated per week
  • • Scaled partner onboarding without adding sales headcount
READ ARCHITECTURE
04PLATFORM OWNERSHIP
500+ ACTIVE ERP USERS

ENTERPRISE SCHOOL ERP ARCHITECTURE

Demonstrated full-lifecycle SDLC platform ownership: stakeholder discovery, relational schema modeling, role-based portals for faculty and admin, and production cloud deployment.

Requirements GatheringRelational DatabaseRole-Based Access ControlFull-Stack SDLCCloud Hosting
DELIVERY HIGHLIGHTS:
  • • 500+ active institutional users
  • • 100% paperless daily attendance and gradebook records
  • • Full lifecycle delivery from paper discovery to deployment
READ ARCHITECTURE
06THE AI QUESTION / DIAGNOSTIC POSTER

SHOULD THISACTUALLY BE AI?

An editorial diagnostic for founders and operators.

01 · Is the process repetitive?
02 · Involves structured decisions?
03 · Does useful data exist?
04 · Requires human judgement?
RECOMMENDED POSTURE
AUTOMATE

Deterministic decisions, high repetition, and clean data make this an ideal candidate for end-to-end automation with n8n/Make pipelines and targeted LLM extraction.

Rule: AI should create leverage, not complexity.
07EXPERIENCE / TIMELINE

WHERE I'VE OPERATED.

From early-stage RevOps loops to enterprise platform architecture.

2026

CLOZZET INDIA

Growth Engineer — AI Solutions & RevOps

Designed and deployed AI-powered automation workflows for brand partnership acquisition, reducing manual prospecting effort by 60%. Built automated outreach and lead-scoring systems generating 3× more qualified brand leads per week.

AI SolutionsWorkflow AutomationCRM SyncHubSpotApollo.ion8n
2024

STUDAI GENIE EDUTECH

Campus Ambassador Leader — Technology Adoption

Led AI-focused outreach campaigns connecting 1,000+ students to hands-on learning opportunities. Organized 10+ workshops on AI and data technologies, translating complex emerging technical topics for non-technical audiences.

AI AdoptionWorkshopsTechnical CommunicationStakeholder Alignment
2023

INDEPENDENT TECHNICAL DELIVERY

Full-Stack Developer & ERP Architect

Built a full-stack institutional school ERP system handling attendance, grading, scheduling, and parent communication for 500+ active users across faculty and administrative roles.

Requirements GatheringSystem ArchitectureRelational DatabaseCloud Deployment
08TECHNICAL REPERTOIRE / THE STACK

THE STACK.

Technology is evidence, not identity. A curated visual composition of the tools, orchestrations, and frameworks I use to engineer solutions.

LANGCHAIN/LANGGRAPH/VOICE AI/ELEVENLABS/n8n/MAKE/HUBSPOT CRM/APOLLO.IO/PYTHON/FASTAPI/NEXT.JS/CREWAI/RAG PIPELINES/MCP/AWS/DOCKER
“The stack is the middle layer. The outcome is the product.”
09PHILOSOPHY / ABOUT
Dhruv Pathak
DHRUV PATHAK · AI SOLUTIONS ENGINEER

BUILDING IS ONLYHALF THE JOB.

“The other half is understanding whether what you build actually solves the problem.”

Based in Ahmedabad, Gujarat, I work with startups, businesses, and international clients across US and UK time zones to design, deploy, and operationalize AI systems.

Whether it is engineering an inbound Voice AI admissions agent that converts international prospects 24/7, automating multi-agent account scoring that saves 10 hours a week, or architecting full-stack ERP software for 500+ users, I focus on frontline adoption and defensible commercial ROI.

Bachelor of Technology in Information Technology — Marwadi University, Rajkot, Gujarat
AI, Data Science, Computational Techniques · Smart India Hackathon Team Lead
10DOCUMENTATION / RESUME
CURATED QUALIFICATIONS

THE STRUCTUREDVERSION.

Experience, technical depth, selected projects, and measurable commercial outcomes compiled in a clean, one-page format.

AI Adoption & RevOps
Multi-Agent Architecture
Client-Facing Delivery