Straion is a centralized rules management platform purpose-built for AI coding agents like Claude Code, GitHub Copilot, and Cursor. It targets lead developers and engineering leaders at teams of 100+ who have already rolled out AI coding assistants and now need them to actually follow organizational standards. The core value of Straion is that it automatically injects the right engineering rules into each agent session — architecture patterns, security policies, and coding conventions — before the first line of code is written. Setup takes less than five minutes and requires no credit card, making it immediately accessible for teams scaling their AI development.
The concrete problem Straion solves is the chaos of scattered rule files across repositories. Many teams rely on CLAUDE.md, AGENTS.md, or .cursor/rules files that quickly become outdated, duplicated, or lost. Developers copy-paste outdated standards, new members miss critical guidelines, and AI agents often ignore rules they cannot find or that have been compacted out of context. This leads to hours of manual course-correction, inconsistent code, and violations slipping through to code review. Straion eliminates this by providing one source of truth that is always current and automatically enforced.
The Centralized Rule Hub is the foundation of Straion. It acts as a single repository for all organizational coding rules, replacing the fragmented approach of maintaining separate CLAUDE.md files in every repo. Teams can import their existing standards or create new rules directly in Straion's interface. Each rule set can be tagged by domain, team, or technology stack, making it easy to manage diverse projects. The benefit is dramatic: no more hunting through wikis, no stale copies, and no more AI agents missing critical guidelines. New engineers and their AI assistants get up to speed immediately because the correct rules are always accessible from one place.
Dynamic Context Selection is Straion's second major feature. Its CLI automatically determines which rules apply to each task based on context such as the repository, team, project domain, and tech stack. When a developer begins a new task, Straion scans the available rule sets and selects only the relevant ones. For example, a feature request in a Node.js service will trigger rules for that stack, while a frontend change pulls UI and accessibility standards. This ensures the AI agent gets precisely the guidance it needs without being overwhelmed by irrelevant rules. The result is faster, more accurate code generation that adheres to your specific standards.
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Task Plan Validation is the third core feature. Before the AI starts writing code, Straion validates its proposed approach against your rules. This preventative step catches violations at the plan stage, saving tokens and time that would otherwise be wasted on incorrect implementations. If the agent's plan violates a security policy, architecture constraint, or naming convention, Straion flags it immediately, allowing the developer to correct course before any code is written. This reduces rework, speeds up development, and ensures that only rule-compliant code reaches code review. Developers reported catching mistakes early, leading to enterprise-ready code at actual 10x speed.
Straion integrates seamlessly with Claude Code, GitHub Copilot, and Cursor. The workflow is simple: first, define your rules in Straion's hub; second, install the Straion skill via CLI into your agent's setup; third, the CLI dynamically fetches relevant rules based on the task context; fourth, Straion validates the agent's plan before execution. The entire setup takes under five minutes. The CLI tool can be installed globally, and the skill connects directly to your organization's rule sets. This automated pipeline ensures that every agent session starts with the correct context and validation, without manual intervention.
For a team managing multiple repositories under the same GitHub organization, Straion eliminates the need to duplicate CLAUDE.md in every repo. Instead, a single set of centrally managed rules applies across all repos, automatically selected by context. New team members no longer miss critical guidelines because their AI agent receives the right rules from the first prompt. In code review, fewer violations slip through because the plan was validated upfront. Teams can scale from 50 to 5,000 developers while maintaining consistent standards. One pilot partner, Dynatrace, uses Straion to align agents across their engineering organization, shipping production-grade applications faster and cleaner.
Straion is built for lead developers, engineering managers, and platform engineers at organizations with 100+ developers who have already adopted AI coding agents. It works with Claude Code, GitHub Copilot, and Cursor, and requires no credit card to start. The free tier allows teams to get started immediately, with pricing for scaling teams available on the website. Straion is funded by Marathon and supported by Austrian innovation grants, reflecting its enterprise-readiness. In summary, Straion provides the infrastructure needed to ensure AI coding agents follow your exact architecture, security, and coding standards — automatically, at scale, and without manual overhead.
Lead developers, engineering managers, and tech leads at organizations with 100+ developers who have already adopted AI coding agents like Claude Code, GitHub Copilot, or Cursor. Also relevant for DevOps and platform engineers responsible for maintaining coding standards across multiple repositories, and for CTOs or VPs of Engineering looking to enforce enterprise-wide AI governance without manual overhead.