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Use case · Enterprise Teams

One review standard across every repository.

Large organizations need AI review that fits procurement and security: their own model provider, single sign-on, audit trails, and the option to run everything inside their network.

Deployment
Cloud or self-hosted
Access
SSO / SAML, RBAC
Model
Your provider
Start free See examples

How enterprise teams use AI code review

Enterprises use AI code review to apply one review standard across many teams and repositories while keeping control of their code and model. Mesrai runs on the company's own LLM provider (bring your own key), supports SSO/SAML, RBAC and audit logs, can be self-hosted, and lets platform teams define organization rules that every repository inherits.

I.

The enterprise code review challenge

  • 01

    Hundreds of repositories, dozens of teams and no consistent definition of a 'reviewed' change.

  • 02

    Security and legal teams won't approve a tool that sends code to an unknown model provider.

  • 03

    Standards live in wikis that reviewers don't read and that no tool enforces.

  • 04

    Mixed Git hosting — GitHub for some teams, GitLab or Azure DevOps for others.

II.

How Mesrai fits enterprise requirements

Bring your own model provider

Reviews run on your OpenAI, Anthropic, Google Vertex AI, AWS Bedrock or OpenAI-compatible account, under your existing data agreements. Your code is never used to train models.

Self-hosted option

Run Mesrai inside your own infrastructure on the Enterprise plan, with your own Git apps and model endpoints.

Identity and audit

SSO via SAML with your identity provider, role-based access control and audit logs on the Enterprise plan.

Governance at scale

Organization rules inherit to every repository and folder. A central standards repository can be referenced from any rule with @repo:, and memories set at organization level apply everywhere.

III.

Real-world scenarios

2 examples

Illustrative examples of the kind of change enterprise teams make every week, and the review comment Mesrai would post.

Scenario 01

Turning the engineering handbook into checks

A platform team owns a 40-page engineering standards document. New services keep violating its logging and timeout rules.

Organization rule
Name: Outbound HTTP calls need timeouts
Scope: File
Severity: High
Instructions:
  Flag outbound HTTP calls (fetch, axios, http clients) without
  a timeout. Follow section 4.2 of
  @repo:platform/engineering-standards/docs/standards.md
MesraiMesrai RulesMUST_FIX

This axios call to the pricing service has no timeout, so a slow dependency can exhaust the worker pool. Set a timeout per section 4.2 of the engineering standards.

Result: The handbook becomes enforced policy on every pull request in every repository, with the source cited in each comment.

Scenario 02

Procurement-ready from the first meeting

Security review asks where code goes, who can access it, and whether it trains a model.

MesraiDeployment choiceSUGGESTION

Self-host Mesrai in your VPC and point it at your existing Bedrock or Vertex AI endpoint. Code stays inside your cloud account; access is through your IdP via SAML; actions are recorded in audit logs.

Result: The tool fits existing cloud, identity and data agreements instead of needing new ones.

IV.

Enterprise rollout

Most enterprises run a four-to-six-week pilot before organization-wide rollout.

  1. 1

    Choose cloud or self-hosted deployment and connect your model provider.

  2. 2

    Configure SSO/SAML with your identity provider and set roles.

  3. 3

    Pilot on three to five teams across your Git hosts.

  4. 4

    Encode your top standards as organization rules; let teams add folder-level rules.

  5. 5

    Review Pulse metrics and finding acceptance with pilot teams, then expand.

V.

Who uses it, and how

Platform / DevEx team
Owns organization rules, model configuration and rollout.
Security & compliance
Approves the deployment model and adds security rules that apply everywhere.
Team leads
Add folder-level rules for their services without touching global policy.
VI.

What to measure in Pulse

Lead time for changes

Compare teams with one consistent definition.

Change failure rate

Track whether consistent review reduces incidents org-wide.

Mesrai suggestions

See which findings teams act on, to tune rules.

VII.

What teams achieve

One review standard across teams and Git hosts

Code and model usage inside your existing agreements

Standards enforced from the document they're written in

Delivery metrics comparable across the organization

VIII.

Enterprise Teams — frequently asked

4 questions

  • Can Mesrai be self-hosted?

    +

    Yes. Self-hosting is available on the Enterprise plan, so the service runs inside your own infrastructure.

  • Which model providers can we use?

    +

    OpenAI, Anthropic, Google Gemini and Vertex AI, AWS Bedrock, and any OpenAI-compatible endpoint, including models you host yourself.

  • Does Mesrai support SSO?

    +

    Yes. SSO via SAML, plus RBAC and audit logs, are included in the Enterprise plan.

  • Is our code used for training?

    +

    No. Your code is never used to train any model. With BYOK, model requests go to the provider you chose under your agreement with them.

Further reading

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