Compliance requirements your engineers and AI agents can actually implement.
RuleMesh defines what every regulation requires across your cloud infrastructure, how to execute it with framework-specific controls, and what evidence proves it was done — ready for engineers, AI agents, and the auditors who’ll verify it.
credit_card_offFree to start. Account required for an API key. RuleMesh never accesses or uploads your source.
The missing layer between the policy and the system.
Legal teams read the law. Engineering teams build the system. Auditors verify after the fact. The technical specification that should connect those three usually does not exist.
RuleMesh defines the requirement from source law, maps it to the control pattern the team should implement, and specifies the evidence a reviewer will expect before the audit starts.
What the law requires
A structured requirement with citation back to the article and paragraph it comes from. When someone asks where it came from, the answer is the source text.
What engineering should do
The control pattern that satisfies the obligation, mapped to the cloud and security frameworks your team already uses.
What evidence proves it
The artefact, log, configuration, or attestation a reviewer will expect to see. The evidence is specified before the work starts, not reconstructed later.
From one MCP command to a shareable evidence signals report.
Four steps. One connected workflow. Your coding agent reads the repository; RuleMesh supplies the requirements and evidence criteria.
Connect your agent
Works with Codex, Claude Code, Gemini CLI, Cursor, and other Streamable HTTP MCP clients.
→Evaluate your repository
Your coding agent reads the repository in its own environment and compares the relevant files with RuleMesh requirements and evidence criteria.
→Review the evidence signals
Review what the agent found, what is partial, and what appears missing against the evidence criteria. Humans make the final determination.
→Track the work in your issue tracker
Findings route into Jira today; GitHub Issues, GitLab, and Linear are next.
View the app on the Atlassian MarketplaceTurn evidence signals into verified engineering work.
Jira integration (live)one of several surfaces
Your coding agent evaluates the repository in its own environment and routes findings into Jira tickets — module coverage, checklists, and evidence tracking where your team already works.
Works with your existing toolsno new dashboard
Engineers do not want another dashboard. Findings land in Jira today — GitHub Issues, GitLab, and Linear are next.
Privacy by designsource stays with your agent
Your coding agent reads your source. RuleMesh does not. The agent reports evidence signals and the file names where signals were detected.
Regulations decomposed into engineering modules.
GDPR is packaged end-to-end — 99 articles decomposed into 191 structured requirements across 7 engineering modules, mapped to cloud controls, security frameworks, and evidence checklists. The EU AI Act is the second regulation in the catalog, broken out by actor role.
An open protocol for machine-verifiable compliance exchange.
RuleMesh structures the work inside an organisation. HCAP is our open protocol proposal for exchanging compliance information across system and organisational boundaries.
Read the HCAP draftarrow_forwardChange the agent. Keep the cited rule.
RuleMesh gives each connected agent the same requirement, control mapping, and evidence criterion. The model can change without asking every team to reinterpret the regulation from scratch.
Read the methodology→A fit if you are implementing now.
RuleMesh is onboarding a small number of teams doing regulatory work in real engineering this quarter — GDPR, the EU AI Act, or both. If that is your situation, the next page should help you decide quickly.
Real implementation window
Your team has engineering capacity to act in the next quarter, not just research the problem.
Real regulatory surface
You are in scope for GDPR, the EU AI Act, or both, and need an implementation path you can defend, not another policy exercise.
Workflow-first adoption
You want to start with the MCP path now, and use Jira if it fits your workflow today while other surfaces expand.
Not a fit if you only want attestations, outsourced compliance services, or a broad multi-framework rollout before one regulation is working in practice.
See if your team is a fit→Start with scope, terms, or the regulation itself.
Use these reference surfaces when you need applicability and definitions before implementation.
Connect the agent you already use. Review the evidence before you commit.
Create a free account, choose your coding agent, and copy the setup command. RuleMesh never accesses or uploads your source.