# Intervieux vs Karat: an AI interviewer or a staffed human one

Karat provides technical interviewing as a service: trained human interviewers conduct standardized technical screens on your behalf, at roughly $200 to $400 per interview, delivering a written report within 24 to 48 hours. Intervieux runs the technical interview itself with AI, live code execution across 8 languages, hidden test cases, and a 5-dimension score generated the moment the interview ends, priced in minute packs instead of per-interview fees.

Karat's model exists because technical interviewing is hard to do consistently at scale with your own engineers, who are expensive to pull off their work and inconsistent as a group even with training. Karat solves that by staffing a dedicated bench of Interview Engineers trained to one rubric, so a candidate at one client company gets evaluated the same way as a candidate at another, regardless of which engineer is on shift that day.

Intervieux solves the same consistency problem differently: instead of standardizing a pool of humans, it removes interviewer variance by having the AI conduct every interview the same way, scored against fixed calibration floors and caps so results don't drift interviewer to interviewer or day to day. Karat's report comes from a person who watched the candidate work through a live problem. Intervieux's report comes from an AI that ran the candidate's actual code and scored the conversation around it.

## The honest verdict

If your hiring bar is senior or staff-level engineering roles where a human's judgment about ambiguous, borderline signals, how a candidate handles being stuck, how they communicate a partial solution, matters more than raw consistency, Karat's staffed human interviewers bring something an AI interview does not yet replicate, and its 600,000+ interview benchmark dataset gives clients a comparison point Intervieux doesn't offer. Choose Intervieux when you want technical screening at a lower cost per interview, with results available the moment the interview ends rather than a 24-48 hour turnaround, and when a candidate's code actually running and passing hidden tests is a signal you want built into the score rather than judged by eye. A company hiring a small number of senior engineers where a wrong hire is expensive may find Karat's human judgment worth the higher per-interview cost. A company screening a larger volume of candidates for defined technical roles will get faster, cheaper, and more consistent results from Intervieux's AI-conducted interviews. Some hiring teams split the difference deliberately, using Intervieux to screen the full applicant pool and reserving Karat, or an internal panel, for the final round on the handful of candidates who make it through.

## Who each one is for

Karat fits companies hiring senior technical talent where they want a dedicated bench of trained human interviewers standing in for their own engineers, with a same-standard rubric applied across every candidate and a benchmark dataset built from 600,000+ prior interviews to compare against. It's built for organizations, including large public companies, that treat interviewer consistency as worth paying a per-interview premium for. Intervieux fits employers who want technical screening built into their own hiring pipeline: AI-conducted interviews with real code execution, scored instantly, feeding directly into a screening rules engine and ATS, at a cost structure based on minutes rather than per-interview fees that scale with a growing hiring volume.

## Side-by-side

| Dimension | Intervieux | Karat |
| --- | --- | --- |
| Who conducts the interview | An AI interviewer via a dedicated conversational agent for the technical interview type | A trained human Interview Engineer from Karat's staffed network |
| Turnaround time | Scored the moment the interview ends | Written report and hire/no-hire recommendation within 24-48 hours |
| Code evaluation | Real code execution (Piston) across 8 languages, hidden and visible test cases, auto language detection | Human-observed problem-solving assessed against a standardized rubric |
| Pricing model | Minute packs: 500, 2,000, or 10,000 minutes; employer access by request | Per-interview fees, roughly $200-$400, with volume bands and a minimum annual commitment |
| Benchmark data | Compares a candidate's score against the Intervieux platform average | 600,000+ technical interviews conducted, used for comparative benchmarking |
| Screening automation | Rules engine acts on challenge score plus 5 interview scores automatically (14 operators, 5 actions) | Delivered as a written narrative report for a human recruiter to act on |
| Custom challenges | Employers can author custom technical challenges with an AI-drafted problem and answer key, test-run before use | Standardized rubric applied by trained interviewers |
| Developer / agent access | Full REST API (13 scopes) plus a hosted MCP server (~40 tools) with OAuth 2.1, PKCE, and Dynamic Client Registration | Not described as a public developer API on its marketing site |

## Pricing, compared as of August 2026

Karat doesn't publish a price list; third-party procurement research puts per-interview rates around $200 to $400, structured in volume bands. A pilot tier of 30 to 100 interviews a year runs roughly $10,500 to $40,000 annually, a mid-volume tier of 100 to 400 interviews runs $28,000 to $136,000, and enterprise multi-year deals at 1,500 to 5,000+ interviews a year can reach $285,000 to over $1.3 million, typically with a minimum annual spend or interview-count commitment. Intervieux publishes minute-pack pricing directly: 500, 2,000, or 10,000 minutes, with employer access granted by request. A company running a small number of very high-stakes senior interviews a year might find Karat's per-interview model easier to budget against; a company running steady volume across many roles will likely find a minute pack more predictable.

## Consistency: staffed rubric vs fixed AI calibration

Karat's core pitch is that a trained Interview Engineer applies the same evaluation bar regardless of which client company or geography the candidate is interviewing for, which solves the well-known problem of engineers on a hiring panel scoring the same candidate differently. Intervieux solves the interviewer-variance problem structurally rather than through training: every technical interview runs through the same AI agent, and scores are bound by calibration floors and caps built to prevent inflation or drift, so two candidates answering similarly will land similarly regardless of time of day or interview load. Karat's consistency comes from a standardized human process; Intervieux's comes from removing the human variable from the scoring step entirely, though a hiring team that specifically wants a human's read on ambiguous signals will find Karat's model closer to what they're used to.

## What the report actually contains

Karat's output is a rubric score plus a written narrative report and a hire/no-hire recommendation, produced by the interviewer who ran the session. Intervieux produces a report scored across 5 dimensions, Overall, Communication, Technical, Behavioral, and Cultural Fit, each with written reasoning behind the number, plus a separate challenge score from the technical exercise itself, with hidden test-case results baked directly into that score rather than inferred from watching the candidate type. A penalty system flags specific issues, like a candidate never running their code before submitting, an abrupt ending, or excessive filler words. Where Karat's narrative report reads like a colleague's assessment, Intervieux's report reads like a scored rubric with the underlying evidence, the actual test results, attached.

## Where the report goes next

Karat delivers its report to a hiring team for a human to read and decide on next steps. Intervieux's screening rules engine can act on a completed technical interview automatically, evaluating the challenge score alongside all 5 interview scores, experience level, salary estimate, key skills, and strengths and weaknesses, with 14 operators, 5 actions, and up to 25 nested conditions across 5 levels of logic, so a strong technical result can auto-advance a candidate's stage or flag them for a recruiter without anyone touching the pipeline manually. For teams building further automation on top of screening results, Intervieux also exposes a full REST API with 13 scopes and a hosted MCP server with roughly 40 tools, so a connected AI agent can pull challenge results or move a candidate forward directly. Karat's public site does not describe an equivalent developer-facing API.

## Authoring the technical challenge itself

Karat's technical screens run against a standardized methodology built and maintained by Karat, applied consistently across every client that uses the service, which is part of the point: a company doesn't design the assessment, it buys a proven one. Intervieux takes the opposite approach and lets an employer author its own technical challenge, with an AI drafting the problem statement and the answer key from a short description, then a test-run before it goes live to candidates. That means an employer hiring for a role with unusual requirements, a specific framework, an internal tool, a niche language, can build a challenge that actually matches the job, rather than relying on a general-purpose rubric designed to work across every client Karat serves. The tradeoff runs the other way too: a standardized methodology built from 600,000+ prior interviews carries a kind of proven reliability that a newly authored, employer-specific challenge hasn't accumulated yet. Intervieux compares an individual candidate's challenge score against the Intervieux platform average, but it does not publish a benchmark dataset at anything close to Karat's cited scale.

## Frequently asked questions

### Does Karat use AI or human interviewers?

Karat's core service is human interviewers, trained Interview Engineers who conduct standardized technical screens. Its site also describes AI-native evaluation for scenario-based assessment, but the primary product is staffed, human-conducted interviews with a 24-48 hour report turnaround.

### How much does Karat cost per interview?

Karat doesn't publish pricing, but third-party procurement research puts per-interview rates at roughly $200-$400, in volume bands, with annual spend ranging from about $10,500 for a small pilot to over $1.3 million for enterprise multi-year deals at 1,500+ interviews a year.

### Can Intervieux run and grade real code like a human interviewer would?

Yes. Intervieux's technical challenges execute real code through Piston across 8 languages, with hidden and visible test cases, hints, and adjustable difficulty. The challenge score feeds directly into the candidate's overall report and the screening rules engine.

### Why would a company pick Karat's human interviewers over an AI interview?

Karat's human interviewers can read ambiguous signals, how a candidate handles being stuck, how they explain a partial solution, that current AI interviews aren't built to judge the same way. Companies hiring senior or staff-level engineers where that judgment matters most often value Karat's model despite the higher per-interview cost.

### Can an employer write a custom technical challenge on Intervieux?

Yes. Employers can describe a challenge and have Intervieux's AI draft the problem statement and answer key, then test-run it before publishing to candidates. Karat instead applies its own standardized methodology consistently across every client rather than letting employers author their own.

## Related pages

- [Intervieux vs HireVue](/compare/intervieux-vs-hirevue)
- [Intervieux vs Paradox](/compare/intervieux-vs-paradox)
- [Frequently asked questions](/faq)
- [Intervieux home](/)

## Run technical interviews that score themselves

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