What I build

Systems, not campaigns.

I build AI-native operating systems across commerce, mobility, GTM and content. Each system solves a real operational problem with product thinking + AI automation.

View resume →

Reusable architecture pattern

The same pattern behind all my products: User Channels → Orchestration → Intelligence → Memory → Actions.

             ┌───────────────────┐
             │   USER CHANNELS   │
             │ Web / WhatsApp    │
             └─────────┬─────────┘
                       ↓
             ┌───────────────────┐
             │   ORCHESTRATION   │
             │ Cloudflare        │
             └─────────┬─────────┘
                       ↓
             ┌───────────────────┐
             │   INTELLIGENCE    │
             │ LLM / AI         │
             └─────────┬─────────┘
                       ↓
             ┌───────────────────┐
             │      MEMORY       │
             │ Supabase / Data   │
             └─────────┬─────────┘
                       ↓
             ┌───────────────────┐
             │     ACTIONS       │
             │ APIs / workflows  │
             └───────────────────┘
01

AI / Product Systems

Company memory, data fabric, AI context, recommendations, commerce operations. Building the intelligence layer behind businesses.

Vridhi Company Intelligence OS

Architecture

Company Memory → Data Fabric → AI Context → Recommendations → Approvals → Execution. Enterprise intelligence layer that turns scattered data into actionable signals.

Data Sources
      ↓
Company Memory
      ↓
AI Context
      ↓
Recommendations
      ↓
Approvals → Actions

Built with: TypeScript · Supabase · LLM inference · Cloudflare

AIArchitectureData

Mera Commerce OS

Live

Commerce data, storefront/admin, orders, inventory, CRM, payments, analytics, AI operator, integrations, marketplace.

Storefront / Admin
      ↓
Application APIs
      ↓
AI Operator
      ↓
Orders / Inventory / CRM
      ↓
Payments / Analytics

Built with: Next.js · Supabase · TypeScript · Vercel

CommerceProductAI
Live demo →

AI Policy & Permission Engine

Architecture

User → Role → Data Scope → AI Scope → Allowed Actions. Enterprise AI governance layer for controlling what AI can see and do.

User → Role
      ↓
Data Scope → AI Scope
      ↓
Allowed Actions
      ↓
Audit → Ledger

Built with: TypeScript · Supabase RLS · Cloudflare

AISecurityReusable

AI Action & Approval Layer

Prototype

AI assistant vs AI operator: identify → propose → approval → execute. Human-in-the-loop governance for production AI systems.

AI identifies opportunity
      ↓
Proposes action
      ↓
Human approval gate
      ↓
Execute → Audit

Built with: TypeScript · LLM inference · Cloudflare Workers

AIAutomationGovernance
02

Fleet / Mobility

Full-stack EV fleet operating system. Fleet management, rider onboarding, KYC, WhatsApp operations, AI automation, document processing.

HYPR Fleet OS

Flagship

AI-powered fleet operations platform connecting rider onboarding, vehicle operations, WhatsApp intelligence, financing and fleet workflows.

WhatsApp / Web
      ↓
Cloudflare Workers
      ↓
Application APIs
      ↓
AI / Intelligence Layer
      ↓
Supabase / D1
      ↓
Fleet Operations
      ↓
Dashboards + Actions

Built with: Cloudflare · Workers · Supabase · LLM inference · WhatsApp · TypeScript

ProductFull-stackAI AutomationLive
Architecture →GitHub →Live Demo →Case Study →

Rider OS + KYC Automation

Architecture

Rider onboarding, KYC, OCR, eligibility, vehicle assignment. 7-step wizard writing to Supabase, R2 storage, local validation.

Phone → KYC → Eligibility
      ↓
Vehicle → Plan → Agreement
      ↓
Payment → Assignment
      ↓
Supabase + R2

Built with: Next.js · Supabase · R2 · Indian ID validation · TypeScript

MobilityAIKYC

Fleet WhatsApp Intelligence

Production-oriented

WhatsApp Groups → WhatsApp API → AI Classification → Operational Signals → Manager Brief → Action. Single transport, wa.example.com gateway.

WhatsApp Groups
      ↓
WhatsApp API → AI Classification
      ↓
Operational Signals
      ↓
Manager Brief → Action

Built with: WhatsApp API · LLM inference · Cloudflare · TypeScript

WhatsAppAIFleet

HyperElectric — EV fleet GTM

Owned GTM from zero: defined ICP and messaging for 3 buyer types (riders, vendors, franchisees), designed onboarding flows, enabled vendor partnerships, built franchise pipeline, and managed investor communications.

GTMRevOpsPMM

View full case study →

03

GTM Engineering

50K-account outbound engine + RevOps. data enrichment, sales intelligence, enrichment, lead routing, campaign operations, revenue infrastructure.

04

Content / Growth Automation

Research → AI → creative → publish → metrics. social scheduling, social automation, SEO, content at scale.

Social Content OS

Production-oriented

Research → Knowledge → Insight → Draft → AI Review → Creative → Publish → Metrics → Learning. social scheduling + AI content engine.

Research → Knowledge
      ↓
Insight → Draft
      ↓
AI Review → Creative
      ↓
Publish → Metrics
      ↓
Learning Loop

Built with: social scheduling · LLM inference · MCP · Notion

ContentAISocial

EV Intelligence Media

Production-oriented

EV research → automated articles → visual generation → SEO → publishing. Content automation at scale.

EV Research
      ↓
AI Article Generation
      ↓
Visual Generation
      ↓
SEO → Publishing

Built with: Next.js · LLM inference · Vercel · MDX

EVContentSEO

AI Research & Intelligence Worker

Production-oriented

Sources → Research → Scoring → Synthesis → Delivery → Content. Automated research pipeline.

Sources → Research
      ↓
Scoring → Synthesis
      ↓
Delivery → Content

Built with: LLM inference · MCP · Playwright · TypeScript

AIAutomationResearch

Compounding growth systems

Built self-reinforcing growth loops that compound over time instead of relying on linear funnel optimization.

Demand GenGrowth

View framework →

How I build

Business problem→Product strategy→Data model→AI / automation→Infrastructure→GTM→Measurement

I don't operate in a single function. I connect the functions — from business problem to working system.

Skills

Product

Product Strategy, Technical PM, User Journey Design, MVP Design, Product Discovery, Productization

AI

AI-native workflows, Agentic systems, LLM API integration, RAG / retrieval, AI memory, AI permissions, Human-in-the-loop

Engineering

Next.js, React, TypeScript, PostgreSQL, Supabase, Cloudflare Workers, Queues, R2, Vercel, REST APIs, Webhooks, workflow automation, WhatsApp API

GTM

GTM Strategy, RevOps, Outbound, data enrichment, sales intelligence, Lead enrichment, Demand generation, Product marketing, Paid media, Lifecycle

Commerce

D2C, Commerce platforms, Marketplace architecture, Payments, Inventory, CRM, Logistics

Mobility

EV fleet operations, Rider onboarding, Fleet management, KYC, Fleet economics

Operator timeline

GTM Engineer — Independent

2023 – Present • Hyderabad

Building GTM systems, outbound workflows, research infrastructure, and execution playbooks for clients. Currently supporting HyperElectric across rider onboarding, vendor partnerships, franchise pipeline, and investor communications.

Marketing Associate — MediaMint

2021 – 2023 • Hyderabad

Managed LinkedIn campaigns generating 500 MQLs monthly through marketing automation/CRM nurture systems. Built lead routing logic connecting ad performance to sales handoff to improve follow-up velocity.

Digital Marketing Manager — Techtonic

2014 – 2020 • Hyderabad

Grew inbound leads 3x through content syndication and paid social while establishing baseline conversion measurement and analytics frameworks.

See the full picture

Architecture = how you think. Case study = why you decided. GitHub = what you actually built. Live product = proof it works.