Case Study

HireFlow

Agentic job-search copilot that matches roles, rewrites resumes, autofills applications, and prepares interviews so candidates reclaim their time.

Next.jsNext.js
Tailwind CSSTailwind CSS
Node.jsNode.js
MongoDBMongoDB
Google Gemini 2.0Google Gemini 2.0
LangChainLangChain
LangGraphLangGraph
PuppeteerPuppeteer

Overview

HireFlow is an agentic job-application assistant my team and I built to automate the repetitive grind of job hunting, from role discovery through interview prep.

Problem

  • Applicants lose 10+ hours per week tailoring resumes and filling identical forms.
  • Most submissions are rejected by ATS filters before a human review.
  • Manual company research and interview prep fractures focus.

Solution

  • LangChain and LangGraph agents orchestrate matching, writing, and filing tasks.
  • Gemini-powered rewriting keeps resumes tailored yet on-brand.
  • Puppeteer automation completes repetitive application flows.

Research & Techniques

  • Benchmarked ATS scoring heuristics across industries.
  • Prototyped compatibility scoring with historical job data.
  • Prompt-engineered Gemini 2.0 for consistent outreach tone.
  • Logged automation sessions to maintain form accuracy.

Results

  • Cut manual application effort by roughly 90% in pilot tests.
  • Achieved a 3× lift in recruiter responses.
  • Collected positive feedback on interview briefing quality.

Key Features

Tap a feature to explore how it supports the experience.

Semantic role matching with compatibility scoring dashboards

Tech Stack

Next.jsTailwind CSSNode.jsMongoDBGoogle Gemini 2.0LangChainLangGraphPuppeteer