Sold by: Ninchi
Ninchi helps organizations adopt AI with accountability by verifying human understanding of AI-assisted software work. It generates artifact-specific comprehension challenges for pull requests, records inspectable evidence, and supports org analytics and governance. Run checks from GitHub, GitLab, Bitbucket Cloud, Ninchi CLI, or MCP-capable editors. Enterprise adds knowledge maps, SSO/SCIM, audit export, IP allowlisting, and BYO LLM.
Overview
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Ninchi Enterprise Dashboard
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Ninchi Narrative Analysis
Ninchi helps organizations adopt AI with accountability by verifying human understanding of AI-assisted work.
As AI accelerates software development, organizations face a new challenge: code can now be generated faster than it can be understood. Traditional code review evaluates the quality of the code itself. Ninchi adds a complementary layer by verifying that the accountable developer can explain the implementation, assumptions, tradeoffs, and potential failure modes before work reaches production.
Rather than attempting to detect whether AI was used, Ninchi focuses on a more important question:
Can the human responsible for this work demonstrate understanding?
Key Capabilities
- AI-generated, artifact-specific comprehension challenges with hidden evaluation rubrics
- Practice, Tracking, Blocking, and Strict verification modes
- Difficulty-weighted Ninchi Score over recorded verified-understanding events
- Team and organization analytics, trends, and repository insights
- Ninchi CLI for terminal, Git hook, and CI checks
- MCP server for agent-capable editors such as Cursor and Claude Code
- Programmatic checks as a separate evidence class (org-configurable toward scores)
- Teach Me learning recommendations
- GitHub, GitLab, Bitbucket Cloud, and direct verification workflows
Enterprise Features
Enterprise customers get advanced governance and organizational visibility, including knowledge maps and member baselines, accountability rollups, SAML SSO and SCIM provisioning, audit-log export, IP allowlisting, bring-your-own LLM, AI-spend accountability views, dedicated support, and deployment options under Enterprise agreement. These capabilities help leaders see where verified-understanding evidence is on record and where it is not without turning Ninchi into a surveillance product.
Why Ninchi
Organizations use Ninchi to move faster with AI while keeping human accountability visible. By verifying understanding before changes reach production, teams create inspectable evidence that AI-assisted work was reviewed by someone who can explain it, surface gaps earlier, and support onboarding and governance with recorded challenge history rather than assumptions.
Ninchi integrates with GitHub, GitLab, and Bitbucket Cloud today, and extends into developer workflows through Ninchi CLI and MCP. Also available on GitHub Marketplace.
Learn more at https://www.ninchi.ai
Highlights
- Verify human understanding of AI-assisted work before it reaches production. Ninchi generates artifact-specific comprehension challenges that confirm developers can explain the code they are responsible for.
- Meet developers where they work: GitHub, GitLab, Bitbucket Cloud, Ninchi CLI, or MCP-capable editors while creating inspectable evidence of human accountability for AI-assisted changes.
- Give leaders organization-wide visibility with analytics, knowledge maps, and Enterprise controls (SSO/SCIM, audit export, IP allowlisting, BYO LLM) so teams can see where verified-understanding evidence exists and where gaps remain.
Details
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Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/month |
|---|---|---|
Seats | End users | $30.00 |
Dimensions summary
This listing bills through a single dimension: Seats, priced per end user. You pay based on the number of users you enroll, so cost scales directly with team size. There are no separate tiers, instance sizes, or usage add-ons to configure in the pricing table. You add or remove seats to match how many people participate in the code-understanding challenge workflow. Ninchi delivers a verification layer that turns code changes into short challenges and records the results as inspectable evidence for your team.
Top-of-mind questions for buyers
A seat is one enrolled end user, tied to their version-control identity. Each person who participates in the code-understanding challenge workflow occupies one seat. You add or remove seats to match how many people take part, and cost scales directly with that count.
Yes. Programmatic checks through the CLI and MCP surface carry hard per-developer quotas over a trailing 30-day window. When a developer hits the limit, checks return a rate-limit response showing when the next check becomes available. Pull-request challenge activity is separate from these programmatic quotas.
No. Billing tracks enrolled seats, not repositories or challenge volume. You connect repositories and run challenges without a per-repository or per-challenge charge in the pricing table. Only the number of users you enroll changes your cost.
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Refunds may be requested within 30 days of the initial purchase by contacting support@ninchi.ai . Refunds are evaluated in good faith based on product usage and customer circumstances. Enterprise contracts and AWS Marketplace Private Offers are governed by their applicable agreement.
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