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ResumeBro — AI Resume Intelligence hero visual

LLM workflows without the wait

ResumeBro — AI Resume Intelligence

Next.js 14 + Server Actions drive ingestion, parsing, and editing, while Firebase auth, Firestore, and Redux Toolkit keep every resume version synced under 100ms latency.

Timeline

Dec 2025 – Present

Schema accuracy

99% typed

Latency savings

-45% API calls

Tech focus

Next.js 14Server ActionsFirebaseLLM

Project gallery

Visual highlights

A quick look at the states, flows, and artifacts that made this launch feel polished.

ResumeBro hero section
Immersive hero that introduces the AI resume workspace at a glance.
Feature highlight grid
Feature grid explains what each module of the platform unlocks for candidates.
Resume generation process overview
Process visualization explains the five-step AI resume generation journey.
Resume generation service overview
Generation service view lists inputs, progress, and automation controls.
Resume parser service
Resume parser module shows extracted entities before validation.
Job description parser service
JD parser screen highlights required skills, responsibilities, and constraints.
Resume generation step 3 — JD parsing
Generation wizard step that confirms parsed JD data before tailoring resumes.
Resume generation step 2 — resume data review
Review screen lets candidates edit parsed resume fields prior to alignment.
Resume generation step 4 — parsed JD review
JD review step ensures requirements are captured before custom generation.
Resume generation step 5 — custom resume output
Custom resume generation screen shows tailored output with export controls.
Parsed resumes list
Table view of parsed resumes with timestamps and quick actions.
Parsed job descriptions list
Parsed JD inventory groups requirements, companies, and creation dates.
Generated resumes archive
Generated resumes table surfaces status, versioning, and sharing options.
Generated resume editor
Generated resume editor supports inline edits, formatting, and AI rewrites.
Parsed JD editor
JD editor lets teams refine responsibilities, requirements, and scoring.
Parsed resume editor
Parsed resume editor surfaces every extracted block for manual review.
Sign-in with Google screen
Google Auth page keeps the workspace gated behind verified accounts.
ResumeBro hero section
Immersive hero that introduces the AI resume workspace at a glance.
Feature highlight grid
Feature grid explains what each module of the platform unlocks for candidates.
Resume generation process overview
Process visualization explains the five-step AI resume generation journey.
Resume generation service overview
Generation service view lists inputs, progress, and automation controls.
Resume parser service
Resume parser module shows extracted entities before validation.
Job description parser service
JD parser screen highlights required skills, responsibilities, and constraints.
Resume generation step 3 — JD parsing
Generation wizard step that confirms parsed JD data before tailoring resumes.
Resume generation step 2 — resume data review
Review screen lets candidates edit parsed resume fields prior to alignment.
Resume generation step 4 — parsed JD review
JD review step ensures requirements are captured before custom generation.
Resume generation step 5 — custom resume output
Custom resume generation screen shows tailored output with export controls.
Parsed resumes list
Table view of parsed resumes with timestamps and quick actions.
Parsed job descriptions list
Parsed JD inventory groups requirements, companies, and creation dates.
Generated resumes archive
Generated resumes table surfaces status, versioning, and sharing options.
Generated resume editor
Generated resume editor supports inline edits, formatting, and AI rewrites.
Parsed JD editor
JD editor lets teams refine responsibilities, requirements, and scoring.
Parsed resume editor
Parsed resume editor surfaces every extracted block for manual review.
Sign-in with Google screen
Google Auth page keeps the workspace gated behind verified accounts.

Project features

Crafted to feel human, performant, and scalable

ResumeBro automates resume tailoring by combining an AI parsing engine, secure workspace, and advanced editors. I led the architecture spanning Next.js 14 App Router, React Server Actions, Firebase auth, Firestore persistence, and Redux-powered editors so users can ingest docs, refine every field, and ship recruiter-ready versions faster.

🧠Feature

Intelligent parsing engine

LLM pipelines turn PDF, DOCX, and JD text into structured JSON with raw, segmented, and block-level reviews plus Zod validation.

ParsingLLM
📊Feature

Secure workspace dashboard

Firebase Auth, server-side sessions, and paginated workspaces let users manage resumes + JDs with analytics and logs.

DashboardAuth
✏️Feature

Advanced editors

Full-resume and JD editors surface nested fields, instant saves, and AI suggestions powered by Redux Toolkit + Firestore.

EditorRealtime
🧪Feature

Unit testing playground

Built-in validation playground lets ops teams inspect parser output at every stage before exporting.

QAAutomation

Services & deliverables

End-to-end partnership

Strategy, engineering, and activation workstreams stayed tightly aligned so the launch felt intentional.

Service

Platform architecture

Mapped ingestion → LLM orchestration → validation → persistence while ensuring every stage streams progress to the UI.

  • Sequence diagrams
  • Schema registry
  • Perf plan

Service

AI pipeline engineering

Designed prompts, guardrails, and evaluation harnesses for the parsing + JD engines with strict schema validation.

  • Prompt library
  • Eval suite
  • Guardrails

Service

Experience design

Crafted the dashboard, resume editor, and JD editor with autosave, diffing, and Firestore-backed analytics.

  • Component system
  • Dashboard
  • Onboarding

Accomplishments

Business impact & program achievements

We measure success with data, ceremonies, and the teams who keep the experience running.

API overhead

-45%

React Server Actions consolidate network chatter to a single round trip per mutation.

Processing speed

3× faster

LLM orchestration + background workers finish drafts three times faster than prior tooling.

User task completion

+35%

Realtime dashboard + editor flow keeps candidates in context until export.

Landmarks

Milestones that shaped the roadmap

From discovery to public launch we ran fixed-length pulses with clear artifacts at every turn.

01Dec 2025

Parsing engine MVP

Shipped ingestion + LLM parsing with Zod validation.

Key moment
02Jan 2026

Workspace launch

Released Firebase-authenticated dashboard with session persistence.

03Feb 2026

Advanced editors

Launched resume + JD editors with autosave and inline AI suggestions.

04Apr 2026

Analytics & QA

Added usage analytics, validation playground, and ops tooling (ongoing).