Hirely

Inspiration

Recruitment is often fragmented across job boards, spreadsheets, emails, messaging platforms, and separate interview tools. Recruiters spend significant time switching between systems, reviewing applications, coordinating interviews, and searching for information, while candidates have limited visibility into their hiring journey.

We wanted to build a smarter recruitment platform that brings the entire hiring workflow into one place. Our goal with Hirely was to combine traditional recruitment management with AI-powered assistance, creating a platform that helps recruiters make better decisions, reduces repetitive work, and gives candidates a smoother experience.

What it does

Hirely is a full-stack AI-powered recruitment platform designed to support the complete hiring workflow.

It provides dedicated experiences for Candidates, Recruiters, Administrators, and Hiring Managers, with role-based access and dashboards.

Key capabilities include:

Candidate profiles and job discovery
Job creation and management for recruiters
Application tracking and candidate review
Interview scheduling and interview tracking
Recruitment messaging and communication
Company and organization management
Recruitment analytics and activity monitoring
AI-powered chatbot assistance
Context-aware AI support for different dashboards
AI-assisted recruitment workflows
Live Interview Copilot capabilities for interview support

The AI assistant is designed to understand the user's role and active dashboard context, while restricting access to authorized data. This prevents the AI from exposing information outside the user's permissions or inventing unavailable information.

How we built it

Hirely was developed as a modern full-stack application with a clear separation between the frontend, backend, data layer, and AI services.

Frontend

React 19
Vite
Tailwind CSS
React Router
Axios
Supabase JavaScript Client
Framer Motion
Lucide React

Backend

ASP.NET Core / .NET 10
Entity Framework Core
PostgreSQL with Npgsql
Supabase JWT authentication
Swagger
Gemini and Vertex AI integrations

The frontend communicates with the ASP.NET Core API through a centralized authenticated API client. The backend handles authentication, authorization, business logic, database access, and AI requests.

For AI features, we designed a context-aware architecture. The backend determines the user's role and dashboard context from trusted authentication and routing information rather than trusting a dashboard value provided by the user. It then creates a limited data snapshot and sends only the relevant information to the AI model. Requests are also validated and rate-limited, with protection against prompt-injection and cross-dashboard access.

The project is also containerization/deployment ready and includes Google Cloud deployment documentation.

Challenges we ran into

One of the biggest challenges was integrating AI into a recruitment platform without compromising security or data privacy.

A normal chatbot can easily become a risk if it is given unrestricted access to recruitment data. We therefore had to design the AI system so that it could understand the user's context while only receiving information that the user is authorized to access.

We also faced challenges around:

Implementing reliable role-based access across multiple user types
Connecting React, ASP.NET Core, PostgreSQL, and Supabase into a single architecture
Managing AI provider authentication and deployment environments
Supporting Gemini API and Vertex AI authentication
Preventing AI responses from generating information when required data is unavailable
Building a consistent user experience across several dashboards
Designing AI features that are actually useful for recruiters instead of simply adding a generic chatbot

Handling AI credentials securely was another important consideration. AI keys and service credentials are kept on the backend and are not exposed through frontend environment variables or browser requests.

Accomplishments that we're proud of

We are especially proud of turning Hirely into more than a simple job portal.

The project brings together recruitment management, communication, analytics, authentication, and AI assistance within one platform. We also built separate role-based experiences so that different users see information and functionality relevant to their responsibilities.

Another major accomplishment is our context-aware AI architecture. Instead of allowing the chatbot to freely access the entire database, the backend determines what the user is allowed to see and provides the AI with only the required information. It can also respond professionally when a request is outside the current dashboard's scope or when the necessary data is unavailable.

We are also proud of building the system with a scalable architecture using React, ASP.NET Core, PostgreSQL, Supabase, and modern AI infrastructure, making Hirely suitable for further development and real-world deployment.

What we learned

Building Hirely taught us that creating an AI-powered application is not only about connecting an API to a chatbot.

We learned how important AI security, authorization, context management, prompt design, backend architecture, and responsible data handling are when AI is working with real business information.

We also gained practical experience in:

Designing full-stack applications with clear frontend/backend separation
Implementing role-based authentication and authorization
Working with PostgreSQL and Entity Framework Core
Integrating Supabase authentication
Building APIs with ASP.NET Core
Integrating Gemini and Vertex AI
Managing AI credentials securely
Designing scalable and maintainable application architecture
Thinking about AI reliability and preventing hallucinated data

Most importantly, we learned that the best AI features are those that solve a real workflow problem and provide useful context at the right moment.

What's next for Hirely

Our vision is to evolve Hirely into a complete AI-powered recruitment ecosystem.

Future improvements include more advanced candidate-job matching, AI-assisted CV and application analysis, intelligent interview preparation, automated interview insights, recruiter recommendations, improved analytics, and more powerful hiring workflows.

We also plan to expand the Live Interview Copilot, strengthen AI-driven recruitment insights, improve automation throughout the hiring pipeline, and continue optimizing the platform for production-scale deployment.

Ultimately, we want Hirely to become a platform where AI does not replace recruiters, but augments their decisions, reduces repetitive work, and helps them focus on finding the right people faster and more effectively. github repo link - https://github.com/mchithna/Recruiter-AI deploy link -https://recruiter-ai-1082676273883.us-central1.run.app/