How it works

Compliance requirements your engineers and AI agents can actually implement.

RuleMesh defines what a regulation requires, maps it to the controls your team should implement, and specifies the evidence that proves it was done. This page shows that loop end to end.

Before the mechanism

RuleMesh is not an AI that scans your project. It is a rules API your coding agent calls.

RuleMesh has no access to your code, your cloud, or your pipeline. It answers questions about regulation over MCP, and the agent you already use (Claude Code, Cursor, Codex) does the reading and the changing; you review it like any other work. Your agent submits evidence signals and file names back so the posture dashboard can render them. Your source code is never sent to RuleMesh.

hubWhat RuleMesh does
  • checkServes structured, versioned rules with the statutory citation still attached.
  • checkMaps each requirement to the cloud and security controls that satisfy it.
  • checkStates the evidence a reviewer will expect to see.
  • checkReceives evidence signals and the file names where your agent detected them.
blockWhat RuleMesh does not do
  • closeRead, scan, upload, or store your source code.
  • closeRun inside your infrastructure, or ask for credentials to it.
  • closeGenerate or interpret requirements with a model. The rules are curated and deterministic, so two agents asking the same question get the same answer.
  • closeChange anything in your project. Your coding agent does that, and you review it.
Three acts

Curate. Deliver. Close the loop.

RuleMesh takes a cited legal obligation, structures it as a rule, serves that rule over MCP to your coding agent, and sends the resulting task and evidence back into the team workflow. That is the mechanism, and it does not change from one regulation to the next.

ACT 01

We engineer cited obligations into structured rules.

Legal text is not a technical specification. RuleMesh takes a cited legal obligation, keeps the article and paragraph attached, maps it to the cloud and security controls the team should implement, and defines the evidence a reviewer will expect.

That closes the first gap. Compliance keeps the legal citation. Engineering gets something it can build from. Audit gets a rule that can be checked before the scramble starts.

  • policyCited back to source law.
  • commitVersioned so requirement changes are visible.
  • apiDelivered in a form engineers and AI agents can act on.
ACT 02

The requirement is delivered over MCP, not trapped in a portal.

Once the rule is structured, it should move directly into the work. RuleMesh serves it over MCP so your coding agent can pull the requirement before it updates code, infrastructure, or the evidence workflow, and a compliance workflow can pull that same cited rule with provenance intact before sign-off.

The direction matters here. Your agent calls RuleMesh; RuleMesh never calls your agent and never reads your code. What comes back the other way is metadata: the evidence signals your agent found and the file names it found them in, never the file contents. This is where the machine-readable form pays off, because the requirement does not have to be rewritten into tickets, prompts, or audit notes at every handoff.

  • codeYour coding agent pulls requirements, controls, and evidence expectations before implementation.
  • account_balanceCompliance workflows can retrieve the cited rule, its mapped controls, and its provenance.
  • hubOne curated rule graph reduces interpretation drift across teams.
ACT 03

The work lands in the systems the team already uses.

Compliance work dies when it lives in a portal nobody opens. RuleMesh pushes the requirement, the checklist, and the evidence signals into the project system the team already works from. Today that means Jira.

The point is not another dashboard. The point is to put the right task in front of the team that owns the surface, with traceability back to the requirement and evidence attached as the work moves.

  • assignmentRequirements become Jira work with the rule reference, owner, and priority already attached.
  • notifications_activeEvidence signals update the ticket as implementation lands and review happens.
  • extensionThe same pattern can extend to other work surfaces over time.
lock
Your coding agent reads your source. RuleMesh does not.
Your coding agent reads your source. RuleMesh does not. The agent reports evidence signals and the file names where signals were detected.

Connect your coding agent to run the loop.

Free to start. Your coding agent reads the repository directly; RuleMesh receives evidence signals and file names, never file contents. Add Jira when the team is ready to run the work inside the project it already uses.

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