HireMind AI

Landing Page
Admin Dashboard
Admin adding Companies that subscribes to the platform
Company creates the Interview and the Rounds Available
The Rounds Set by HR
Question that are generated by AI for aptitude and can also generate for coding rounds too
For Reference when verification failed due to wrong person attending the interview
Candidates must Verify themselves by uploading the ID proof and their onspot image and AI compares the face and name in ID and actual name
After both Face and Name verifies then only he can proceed to the interview that is scheduled
Tech Interview will be conducted by AI it asks questions based on Resume and the role they are taking
We can respond through speech and not only during verification the camera is on but for all rounds both the camera and mic is on .
When Multiple Faces detected there comes a warning. If the warning exceeds 3 then they are disqualified.
When you exit the full screen there comes a warning even if you switch tabs there will be warning
HR's can view the response

Inspiration

Hiring processes are often time-consuming and inconsistent. Recruiters must screen many candidates, conduct multiple interview rounds, and manually evaluate responses. This can introduce delays and potential bias in decision making. We wanted to build a system that could automate early-stage interviews while maintaining structured evaluation and fairness.

What it does

HireMind is a multi-modal AI interview agent that automates candidate screening through multiple rounds including aptitude tests, group discussions, coding assessments, AI-driven HR and technical interviews, and final live human interviews, while generating structured and unbiased evaluations to help recruiters make scalable hiring decisions.

How we built it

HireMind is built as an AI-driven interview system where Claude serves as the core LLM backbone for generating interview questions, analyzing candidate responses, and producing structured evaluations. The platform supports multiple interview rounds including aptitude tests, group discussions, coding assessments, AI HR interviews, AI technical interviews, and final live human interviews.

The frontend is built using Next.js to provide an interactive interview interface for candidates. The backend is developed with FastAPI, which manages interview workflows, processes candidate responses, and communicates with the AI model. We used PostgreSQL to store candidate information, interview responses, and evaluation results.

Key libraries and tools used in the system include SQLAlchemy for database operations, Pydantic for data validation, and Uvicorn to run the backend server. Together, these technologies enable the system to dynamically adapt interview questions, analyze responses, and generate structured scoring reports for recruiters.

Challenges we ran into

One challenge was designing a system that could dynamically adapt interview questions while maintaining structured evaluation criteria. We also faced challenges integrating multiple services across cloud platforms and ensuring smooth communication between the frontend, backend, and AI components.

Accomplishments that we're proud of

We built a working AI-powered interview platform that automates multiple stages of the hiring process. HireMind can conduct several interview rounds including aptitude tests, group discussions, coding assessments, AI HR interviews, AI technical interviews, and even support a final live human interview. We successfully integrated Claude as the core LLM to dynamically generate interview questions, analyze candidate responses, and produce structured evaluation reports that help recruiters screen candidates more efficiently.

What we learned

During the development of HireMind, we learned how to design AI-driven workflows that manage different interview stages and interact effectively with large language models. We also gained experience building full-stack systems, integrating AI for dynamic analysis, and designing structured evaluation pipelines that simulate real-world hiring processes.

What's next for HireMind AI

Next, we plan to add an intelligent resume shortlisting stage before the interview pipeline begins. The system will automatically filter candidates based on criteria such as CGPA, required tech stacks, number of internships, and relevant skills, allowing recruiters to quickly identify suitable candidates before proceeding to the interview rounds.