Co-founder
Profile summary: Pinterest • Machine Learning Engineer II · Master of Engineering - MEng at Massachusetts Institute of Technology
NextByte (YC W25)
NextByte provides an AI‑first interview platform that replaces algorithmic tests with live, collaborative coding challenges where candidates can use AI copilots, while interviewers assess problem‑solving and communication via voice‑driven discussions. The system automatically scores code quality, AI‑tool usage, and conversation metrics, delivering rubric‑based analytics dashboards for faster, data‑driven hiring of engineers.
- Artificial Intelligence
- Developer Tools
- Enterprise Software
- HR Technology
- Software Only
Updated 5 months ago
Funding
Raised to date
$500KRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
across 1 round
Incomplete round history. $500K of the $500K reported total isn’t matched to a known round (1 known round has an undisclosed amount).
RoundDateAmountValuationInvestors
Founders
Product
Problem
Traditional technical interviews rely heavily on memorized algorithms and subjective assessments, which do not reflect the real‑world coding skills engineers use today. Hiring teams also lack efficient ways to evaluate a candidate’s ability to leverage AI‑powered development tools and collaborate in realistic coding environments.
Solution
NextByte offers an AI‑first interview platform that replaces abstract algorithm tests with practical coding challenges, conceptual questions, and AI‑tool usage assessments. Candidates work in a live, collaborative coding environment where they can invoke AI assistants, while interviewers conduct voice‑driven discussions to probe problem‑solving approaches. The platform automatically analyzes code quality, tool usage, and communication, generating rubric‑based scores and analytics dashboards for fast, data‑driven hiring decisions. Built by MIT engineers, NextByte also provides a “Magic Import” tool that lets recruiters import candidate work samples for deeper evaluation. By focusing on real‑world skills rather than memorization, the solution helps companies identify engineers who can “vibe code” and work effectively with modern development stacks.
Target Audience
Engineering hiring managers, recruiters, and talent acquisition teams at technology companies that need to evaluate software engineers’ practical abilities and AI‑tool proficiency.
Features
- Voice‑driven interview discussions to assess conceptual understanding and problem‑solving approach
- Live collaborative coding environment with built‑in support for AI copilots and code‑generation tools
- Automated analysis of code quality, AI‑tool usage, and communication metrics
- Rubric‑based scoring and analytics dashboards for quick talent comparison
- Customizable interview templates and evaluation criteria to match specific role requirements
- “Magic Import” feature for importing and assessing candidate code samples or project artifacts
- Secure, role‑based access control and encrypted data storage