Inspiration
For the applicant side, the resume pdf's they send are not guaranteed that they actually match the jobs. The skill tree is meant to help point out weak points or spots to improve, and the interview prep allows the applicants express themselves to the best of their ability, in a way that aligns with the company's expectations. For the recruiters, AI ranking allows easy access to filter fitting vs underqualified candidates.
What it does
Builds a skill tree for the skills of the applicant based on their CV and github repositories, and provides interview preparation using Gemini and ElevenLabs for specific job postings.
How we built it
We created a plan that consists of 3 phases and divided the work accross the 3 members. We followed an agile approach, and almost all were completed (up to phase 2.5).
Challenges we ran into
Implementing Solana for additional security and fine-tuning the scripts for the Gemini API use took some time but we ended up overcoming them.
Accomplishments that we're proud of
Our main UI looks simply out of this world, and data integrity accross MongoDB and the blockchain.
What we learned
We learned how to implement AI into our workflow and use it to its upmost potential (within the project's capabilities), and gained experience in working with other AI tool API's such as ElevenLabs. Also, we learned how to use tailwing and design interactive designs.
What's next for IstanbulsFinest
IstanbulsFinest's next set up updates will consist on imrpoving the skill tree's categories, and the style of data extraction that leads to the creation of the skill tree.
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