Domain

HireForge AI

HireForge automates technical recruiting in three stages: 1. **Analyze** — parse resume PDFs and evaluate fit against role requirements (AI/ML, frontend, backend) 2. **Decide** — AI agent returns selection decision with detailed skill-matching feedback 3. **Act** — optionally send selection/rejection emails and schedule Zoom interviews

Python Streamlit

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HireForge AI

AI recruitment agent team by Sharad Khare.

HireForge AI is a Streamlit-powered hiring workflow that analyzes resume PDFs against engineering role requirements, makes selection decisions, and optionally sends emails or schedules Zoom interviews when credentials are configured.

Built and maintained by Sharad Khare — AI strategist, full-stack developer, and creator of practical agent workflows.

What this project does

HireForge automates technical recruiting in three stages:

1. Analyze — parse resume PDFs and evaluate fit against role requirements (AI/ML, frontend, backend)

2. Decide — AI agent returns selection decision with detailed skill-matching feedback

3. Act — optionally send selection/rejection emails and schedule Zoom interviews

Why Sharad Khare built HireForge AI

Resume screening is repetitive and role-specific criteria vary widely. HireForge demonstrates how an Agno agent team can standardize technical hiring workflows while keeping email and scheduling integrations optional.

How it works

Resume PDF Upload + Job Role Selection
   │
   ▼
Resume Analyzer Agent (OpenAI GPT-4o)
   └── JSON selection decision + feedback
   │
   ▼
Optional: Email Agent (EmailTools)
   ├── Selection confirmation
   └── Rejection with feedback
   │
   ▼
Optional: Zoom Scheduler Agent
   └── Interview booking via Zoom API

Supported roles

| Role | Key Skills Evaluated |

|------|---------------------|

| AI/ML Engineer | Python, PyTorch, ML/DL, MLOps, RAG/LLM |

| Frontend Engineer | React/Vue/Angular, TypeScript, responsive design |

| Backend Engineer | APIs, databases, cloud, Docker/Kubernetes |

Features

PDF resume text extraction and AI-powered skill matching
Three predefined engineering role profiles
JSON-structured selection decisions with feedback
Optional email notifications via EmailTools
Optional Zoom interview scheduling via Zoom OAuth API
Core analysis works with OpenAI key only — email/Zoom are opt-in

Quick start

cd hireforge-ai
pip install -r requirements.txt
streamlit run app.py

Required API keys

OpenAI API key — resume analysis (required)

Optional integrations

Email sender + app password + company name — selection/rejection emails
Zoom Account ID, Client ID, Client Secret — interview scheduling

Project structure

hireforge-ai/
├── app.py
├── hireforge/
│   ├── config.py
│   ├── roles.py
│   ├── resume.py
│   └── agents.py
├── requirements.txt
├── pyproject.toml
└── README.md

Topics

Sharad KhareHireForge AIAI recruitment agentresume analysis AItechnical hiring automationZoom interview schedulerrecruitment email agentmulti-agent hiringStreamlit recruiting appAgno recruitment teamtalent screening AI.

Who this is for

HR teams screening technical engineering candidates
Startup founders hiring their first engineers
Recruiters evaluating AI/ML, frontend, and backend resumes
Developers learning agent-based workflow automation for hiring

Use cases

Upload a resume and get an AI selection decision with skill gap analysis
Send automated rejection emails with constructive feedback
Schedule Zoom interviews for selected candidates
Compare candidates against standardized role requirement profiles

Author

Website: sharadkhare.in

License

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bash

cd hireforge-ai
pip install -r requirements.txt
streamlit run app.py