How We Built Our Own AI Interview Grader (No GPT)
Most "AI interview" tools are a thin wrapper around GPT. We did the opposite — we trained our own generative model, from scratch, to run the whole interview: ask the questions, grade your answers, and explain them. Here's how it works, what went wrong on the way, and why the harder road was worth it. When you finish an answer in Peakblick, something has to decide: did that actually cover what the…
Most AI interview tools are built on top of GPT. The opposite approach was taken, training an entirely new generative model from scratch to handle the entire interview process. This model can ask questions, grade answers, and provide explanations. The key challenge is creating a model that can accurately assess a candidate's responses consistently, without being affected by API changes or pricing fluctuations.
Additionally, the model should be owned and controlled by the company, rather than rented from a third party. The result is a compact, self-trained generative model that runs the whole interview, generating both questions and answers. The model assesses the answers based on what a strong response should look like, rather than making assumptions or drawing conclusions on its own.
This approach ensures that the grading is accurate, trustworthy, and provides concrete feedback that candidates can use to improve their performance.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
