NinchiApp installs statistics

Ninchi helps organizations safely scale AI adoption by creating auditable records of human understanding and decision-making around AI-generated work. As AI outputs scale faster than enterprise controls, Ninchi fills the governance gap.

Code review checks whether the code is correct. Ninchi checks whether the author understands the code. In AI-assisted workflows, it's possible to submit code that works without fully understanding why. Ninchi adds a lightweight verification at that point.

Capabilities

Ninchi verifies that developers understand the AI-assisted code they submit before it reaches production.

Unlike traditional code review tools that analyze code, Ninchi evaluates the accountable developer through artifact-specific comprehension challenges.

Features

• AI-generated, artifact-specific comprehension questions • Hidden evaluation rubrics • Practice, Tracking, Blocking, and Strict policy modes • Difficulty-weighted Ninchi Score • Team and repository analytics • Enterprise governance and audit evidence

Supported platforms:

• GitHub • GitLab • Bitbucket Cloud

Benefits

Verify Understanding

Ensure developers can explain the code they submit—not just generate it.

Increase Confidence

Focus review effort where understanding is weakest while allowing well-understood changes to move quickly.

AI Governance

Create auditable evidence that AI-assisted code was reviewed by a human who demonstrated understanding.

Preserve Knowledge

Build organizational memory by tracking demonstrated expertise across repositories and teams.

Getting Started

Requirements

• Install the Ninchi GitHub App • Repository administrator permissions • Public Beta

Setup

• Install the GitHub App. • Connect your GitHub organization. • Configure repositories and policies. • Developers begin receiving comprehension challenges.

Typical setup takes under 10 minutes.

Example Prompts

• "Why did you choose this implementation?" • "What happens if this API call fails?" • "What edge cases does this validation handle?" • "How does this change affect authentication?" • "What assumptions does this code make?"

Every challenge is generated specifically for the submitted pull request and evaluated against a hidden rubric.