We’re building SiClaw (https://github.com/scitix/siclaw), an open-source AIOps platform designed to handle the complexity and security requirements of real-world infrastructure.
While building on our previous experience with Pi-Agent, we realized that for AIOps to be truly production-ready, it needs more than just LLM orchestration. We focused on four key areas where we felt existing tools (like OpenClaw) needed more rigor:
1. Security Governance
A strict permission layer between agents and infrastructure: read-only by default, command whitelists, per-action approval for writes, and workspace-isolated credentials to protect production environments.
2. Multi-tenant Team Collaboration
Built for enterprise teams with multi-workspace support, multi-user management (SSO/OAuth2), and isolated AgentBox sandboxes for different teams and environments.
3. From Reactive to Proactive Operations
Integrates with mainstream monitoring and alerting systems to detect anomalies, automatically generate diagnostic plans, and execute remediation actions—moving from reactive to autonomous operations.
4. Deep Diagnostics
A hypothesis-driven 4-stage diagnostic engine: Context collection → Hypothesis generation → Parallel validation → Root-cause conclusion. Bringing “Deep Research” capabilities into real-world operations.
We’re in the early stages and eager for feedback—especially on our security model and how we handle diagnostic hypotheses.
SherryWong•2h ago
While building on our previous experience with Pi-Agent, we realized that for AIOps to be truly production-ready, it needs more than just LLM orchestration. We focused on four key areas where we felt existing tools (like OpenClaw) needed more rigor:
1. Security Governance A strict permission layer between agents and infrastructure: read-only by default, command whitelists, per-action approval for writes, and workspace-isolated credentials to protect production environments.
2. Multi-tenant Team Collaboration Built for enterprise teams with multi-workspace support, multi-user management (SSO/OAuth2), and isolated AgentBox sandboxes for different teams and environments.
3. From Reactive to Proactive Operations Integrates with mainstream monitoring and alerting systems to detect anomalies, automatically generate diagnostic plans, and execute remediation actions—moving from reactive to autonomous operations.
4. Deep Diagnostics A hypothesis-driven 4-stage diagnostic engine: Context collection → Hypothesis generation → Parallel validation → Root-cause conclusion. Bringing “Deep Research” capabilities into real-world operations.
We’re in the early stages and eager for feedback—especially on our security model and how we handle diagnostic hypotheses.
Resources:
GitHub: https://github.com/scitix/siclaw
Website: https://www.siclaw.ai/
Slack: https://join.slack.com/t/siclaw-scitix/shared_invite/zt-3s3k...
I'll be around to answer any questions!