AI Automation & AI Product Builder

ZerotoShipped

I turn ideas and business problems into working systems: products, automations, and AI tools, built end to end and shipped.

Core Focus

Most AI products are a chatbot wrapped around a workflow. I build the workflow first, then decide where AI actually earns its place.

Selected Work

A curated set of systems I've taken from problem to shipped.

01AI Product

PlumResume

An AI CV and cover-letter product, built end to end, from problem validation to a deployed application.

Independently built & deployed

The problem

Most resume tools generate generic, keyword-stuffed text that reads the same for every applicant. Job seekers spend hours manually rewriting their CV and cover letter for every role, with no real guidance on what actually gets them past a first screen.

What it does

PlumResume takes a job description and a candidate's background, then generates a tailored CV and cover letter. Built end to end: UX, data model, and the AI layer, from problem validation through a deployed, working application.

Built with

  • Next.js
  • TypeScript
  • Tailwind CSS
  • Supabase
  • Postgres
  • Anthropic API
  • Vercel
An AI CV and cover-letter product, built end to end, from problem validation to a deployed application.

What I Build

Five areas, one process

01 / 05

AI Products

From problem definition to a working product: UX, product logic, and AI integrated from day one, not bolted on after.

  • Product Design
  • Next.js
  • AI Integration
  • Deployment
02 / 05

Business Automation

Turning repetitive operational processes into reliable, monitored systems that run without babysitting.

  • Workflow Design
  • APIs
  • Databases
  • Reliability
03 / 05

GTM / RevOps Systems

Lead, CRM, prospecting, and outreach workflows built for sales operations, not demos.

  • CRM Integration
  • Lead Routing
  • Approval Flows
  • State Management
04 / 05

Applied AI

Document intelligence, extraction, and classification, with human review where model confidence drops.

  • RAG
  • Extraction
  • Confidence Thresholds
  • Human-in-the-loop
05 / 05

Technical AI Systems

Agents, tool use, evaluation, and the guardrails that keep them predictable under real conditions.

  • Tool Use
  • Evaluation
  • Observability
  • Testing

How I Work

Start with the actual problem, not the AI feature. Understand the workflow before touching the stack.

About

Ankit Kaushik
Focus
AI Product Building, AI Automation
Background
Business Development, Marketing, Operations, GTM and Sales
Currently
Deepening technical depth: Python, APIs, AI systems

I didn't start in software.

My background is in business development, marketing, international business, and operations, understanding how a business actually works before I ever touched a line of code.

That's the part most technical portfolios skip: knowing why something should be built, not just how.

More recently I've moved deeper into AI product building, automation, and technical implementation: learning Python, working with APIs, databases, and AI/LLM systems, and shipping products like PlumResume end to end, from validation through deployment.

Contact

Have a problemworth building?

Ankit Kaushik
GitHub© 2026 Ankit Kaushik. All rights reserved.

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