How does the assessment process work?

Candidates enter a realistic codebase, review a pull request, and leave comments on bugs, refactors, and security risks. They submit their review, and the AI agent opens a revised PR addressing their comments. This loop continues until time expires or candidates feel the code is ready to approve.

Can assessments be customized for different roles?

Yes. Assessments can be calibrated by difficulty level (intern to principal), specialization (frontend, backend, infrastructure, security, platform), and programming languages, allowing you to match the assessment to the specific role you are hiring for.

What does the reporting show?

Reports connect candidate comments to code quality, risk detection, revision judgment, and practical hiring recommendations. The platform also shows how efficiently candidates work with AI, tracking token use and estimated costs.

Recruiting & ATS

Merge

AI-native code review assessments

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A 30-minute online code review assessment that helps engineering teams hire engineers who can actually review code.

Overview

A look at mergeoa.com

Merge turns code reviews into an assessment involving real engineering work to produce hiring-ready signals. Candidates review pull requests and leave comments on bugs, refactors, and security risks, while an AI agent simulates a real engineer by addressing their comments in realtime.

The platform allows custom assessments calibrated to specific roles by difficulty level, specialization, and programming language. Candidates enter a realistic codebase, review a PR, submit comments, and the AI opens revised PRs for them to evaluate, creating a loop that continues until time expires.

Merge provides comprehensive reporting that connects candidate comments to code quality, risk detection, revision judgment, and hiring recommendations. The platform uniquely shows how efficiently candidates work with AI, tracking token use and estimated costs.

Feature notes

Real pull request review loop with AI agent simulation
Custom assessments by difficulty, specialization, and language
Comprehensive scoring and reporting
Multiple difficulty levels from intern to principal
Specialization options in backend, frontend, infrastructure, and more

Pricing

Pricing model: Contact for pricing

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Merge at a glance

Community votes: 0
Followers: 0

Merge metrics

Inspection sheet for mergeoa.com: Ahrefs Domain Rating and Majestic link metrics, with the delta since the last inspection.
Metric	Value
Domain Rating	1 no change since last check
Trust Flow	5 no change since last check
Citation Flow	23 no change since last check
Referring domains	56 no change since last check
External backlinks	178 no change since last check

Domain Rating by Ahrefs inspected 6 Nov 2026, adjusted 1 Nov 2026. Primary topic: Reference/Knowledge Management (4). Majestic inspected 1 Nov 2026, adjusted 1 Nov 2026. Link data: Majestic. Trust Flow, Citation Flow and Topical Trust Flow are trademarks of Majestic-12 Ltd.

Merge domain diagnostics

Run through the diagnostics

Public RDAP record, last read 6 Nov 2026, 04:02 UTC.
Domain age	4 months
Registered	13 Jun 2026
Expires	13 Jun 2027
Registrar	IONOS SE
DNSSEC	Not signed

Run the full check on mergeoa.com

Merge post-launch diagnostics

Measured after Merge went live on Launching Pro on 1 November 2026.

Domain Rating (Ahrefs): 1 no change since launch; 1 at launch (1 Nov 2026), 1 on 6 Nov 2026
Trust Flow (Majestic): 5; First measured 1 Nov 2026
Referring domains (Majestic): 56; First measured 1 Nov 2026

Day 5 since launch. Next receipt: day 30, 1 Dec 2026. The figures report a change; they do not say what caused it, and many things can. No figure here is a guess.

Biggest gains on Launching Pro

Launch tips, free to read

The playbook on Launching Pro lists what to prepare, what to post on launch day and where else to list your product.

Before the day
Launch day
That week
Beyond launch

See the launch playbook

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FAQ

How does the assessment process work?: Candidates enter a realistic codebase, review a pull request, and leave comments on bugs, refactors, and security risks. They submit their review, and the AI agent opens a revised PR addressing their comments. This loop continues until time expires or candidates feel the code is ready to approve.
Can assessments be customized for different roles?: Yes. Assessments can be calibrated by difficulty level (intern to principal), specialization (frontend, backend, infrastructure, security, platform), and programming languages, allowing you to match the assessment to the specific role you are hiring for.
What does the reporting show?: Reports connect candidate comments to code quality, risk detection, revision judgment, and practical hiring recommendations. The platform also shows how efficiently candidates work with AI, tracking token use and estimated costs.

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