Klanex: Decoupling LLM Reasoning from Production Execution

Research context and background

Klanex is a tool designed to make artificial intelligence agents more reliable when they perform real-world tasks. It solves common problems that happen when developers try to connect large language models directly to production systems. These problems include the AI making up fake data, connections timing out while the AI thinks, and security risks from exposed passwords. Klanex fixes these issues by separating the AI's thinking process from the actual execution of commands. It validates requests quickly, queues them safely, runs them with built-in error handling, and reports results securely. This architecture ensures that every API call is queued, retried if needed, supervised, and recorded for future reference.

Benefits

Klanex offers several key advantages that improve the stability and safety of AI agents:

• Instant Validation and Self-Correction: The system checks every request against a strict format. If the AI makes a mistake, it gets an instant hint on how to fix it without needing human help. This prevents small errors from breaking entire workflows.
• Built-in Retries and Error Handling: Temporary network issues or server errors are handled automatically. The system uses smart retry logic and circuit breakers to ensure tasks complete even when things go wrong. Permanent errors fail fast so developers can fix the root cause.
• Human Approval for Dangerous Actions: Critical tasks like deleting data or processing refunds can be paused until a human approves them via Slack. This adds a safety layer to prevent accidental damage.
• Secure Credential Management: API keys are encrypted immediately upon arrival. They are only decrypted in memory for the short time needed to run a task and are hidden everywhere else. This protects sensitive information from leaks.
• Automatic Replay Capability: If a system goes down, failed tasks can be replayed without asking the AI to think again. This saves time and money by avoiding duplicate AI costs.
• Complete Audit Trail: Every single step, decision, and result is recorded. This provides a clear history for compliance and debugging needs.
• Seamless Integration: Klanex works with popular tools like Slack and Jira. It also integrates easily with coding environments like VS Code and Claude Desktop through a standard protocol.

Use Cases

Klanex is designed for teams that want to deploy AI agents into production environments safely. Here are some common ways it is used:

• Customer Support Automation: AI agents can handle customer refunds or updates. If a refund is too large, the system can pause and ask a human to approve it before the money moves.
• Internal IT Operations: Agents can manage cloud resources or server configurations. The system ensures that no destructive command runs without proper validation and logging.
• E-commerce Workflows: Agents can process orders or update inventory. The built-in idempotency feature ensures that a network glitch does not cause a customer to be charged twice.
• Development and Testing: Developers can test AI agents without worrying about breaking their production databases. The system catches invalid requests early and provides clear feedback.
• Enterprise Compliance: Teams that need to prove their AI actions are safe can use the full audit trail. Every decision is logged and can be reviewed by auditors or managers.

Pricing

Klanex uses a flat monthly pricing model. You pay for the number of executions rather than the number of AI tokens used. Retries and rejected requests are always free.

• Free Plan: Costs $0 per month. Includes 1,000 executions, a 7-day history, up to 5 retries per call, and a limit of 2 requests per second. This is great for testing the tool.
• Starter Plan: Costs $19 per month. Includes 20,000 executions, execution replay, a 30-day history, up to 10 retries, and a limit of 10 requests per second. This is ideal for your first production agent.
• Pro Plan: Costs $99 per month. Includes 200,000 executions, execution replay, a 90-day history, up to 10 retries, and a limit of 50 requests per second. This is for agents handling high volume.
• Enterprise Plan: Offers custom pricing for large teams. It includes features like single sign-on, custom service level agreements, custom data retention, and priority support.

Vibes

While specific customer testimonials are not detailed in the available information, the product has received positive attention for solving critical reliability issues in AI development. The approach of decoupling reasoning from execution addresses a major pain point for developers building production-grade agents. The free tier allows users to explore the full reliability engine without needing a credit card, which lowers the barrier to entry. The integration with popular tools like Slack and Jira suggests it is well-received by teams already using these platforms. The clear pricing structure and focus on security features like human-in-the-loop approvals indicate a product built with enterprise needs in mind.

Additional Information

Klanex is available as a Model Context Protocol server. This means it can be added to any MCP-capable client such as Claude Code, Claude Desktop, Cursor, VS Code, or Windsurf. No extra coding or glue code is required for the hosted endpoint. Official SDKs are available for TypeScript and Python for users who need more control. The system also supports direct HTTP calls from any client. The company focuses on providing a robust lifecycle for every API call, ensuring that calls are queued, retried, supervised, and recorded. This architecture is designed to handle the unpredictable nature of AI models while maintaining the reliability required for production systems.