Karat built its reputation on outsourcing technical interviews at scale, but engineering leaders in 2026 are asking harder questions: Does a standardized interview process actually identify AI-native engineers? And is the cost-per-interview model sustainable when hiring velocity matters more than ever? If you're evaluating alternatives, here's what's actually worth your time.

Karat's model, hiring a network of "interview engineers" to conduct structured technical screens, made sense in the pre-AI era when the goal was consistent evaluation of a relatively static skill set. The friction points teams report today are predictable: limited flexibility in assessment design, per-interview pricing that compounds at volume, and evaluation frameworks that weren't built to assess how candidates actually work alongside AI tools. When 67% of engineering teams report that AI coding assistance is now standard workflow, an interview process that ignores that reality is selecting for the wrong signals.

Not every Karat alternative will fit your specific context. Before committing, run each option through these questions:

The third question is the one most platforms in this list can't answer well yet. The industry is still running assessments designed in 2018 on candidates who are operating in 2026. That gap is where hiring signal degrades fastest.

Here's the uncomfortable truth about technical hiring in 2026: most interview platforms, Karat included, are measuring the wrong things. They evaluate raw algorithmic problem-solving in isolation, when the actual job involves orchestrating AI tools, reviewing generated code for correctness and security, debugging outputs from systems like GitHub Copilot or Cursor, and making architectural decisions about when to lean on AI versus write from scratch. Research from McKinsey has consistently shown that AI augmentation multiplies the output of skilled engineers far more than it replaces their judgment. The engineers your team needs are the ones who can operate as a force multiplier inside that augmented system, not just the ones who can invert a binary tree on a whiteboard in 12 minutes. This matters for platform selection. An alternative to Karat that simply runs the same assessment format in a different interface isn't solving the right problem. The better question is: which platforms are rethinking what technical competency looks like in an AI-augmented workflow?

To be fair: Karat has genuine value for specific use cases. If your hiring volume is high enough that internal engineers running interviews creates real capacity drain, and if the roles you're filling are well-defined enough that standardized assessments work, Karat's outsourced model reduces operational load. Karat reports that companies using their platform see significant reductions in time-to-interview, which matters when candidates are getting multiple offers in days. The case for switching is strongest when:

If your organization is moving toward smaller, higher-leverage engineering teams where every engineer ships more with AI assistance, Nextdev is the only platform on this list built to evaluate that specific capability from the ground up. For teams that need volume screening fast and have internal interviewers to run live sessions, CoderPad is the most flexible self-serve option. Interviewing.io remains the gold standard for senior hiring where depth of signal justifies the premium. The market is shifting toward fewer but better hires, and the hiring infrastructure you choose now will determine whether you find those engineers before your competitors do.