What is Tuning Engines?

Tuning Engines is a unified AI control and governance layer for teams building production intelligence across models, agents, tools, and fine-tuned systems. It brings together the full AI lifecycle—inference, model routing, fallback policies, fine-tuning jobs, datasets, evaluations, model imports and exports, custom models, agents, MCP servers, reusable skills, guardrails, AGT YAML policies, data capture, runtime traces, usage analytics, API keys, billing, team roles, and integrations—into one governed platform. Built by CerebrixOS, it helps organizations move beyond isolated AI experiments into a secure, observable, cost-aware, and extensible AI operating layer.

Who it's for

• Developers who need OpenAI-compatible APIs, Anthropic-compatible routes, CLI workflows, MCP access, coding-agent integrations, and resource catalogs for models, agents, tools, and skills.
• Teams that want to connect Claude Code, OpenCode, Aider, Cline, Roo, Continue.dev, Cursor, VS Code, Windsurf, and other AI workflows through a single governed platform.
• Admins who require production controls like role-based access, per-key budgets, rate limits, routing profiles, fallback rules, guardrails, policy-as-code, credential sources, auditability, usage traces, billing controls, tenant isolation, and team management.

Key features

Universal inference and model routing

Route tasks to the right model based on economics, reliability, and workflow fit. Tuning Engines supports OpenAI-compatible and Anthropic-compatible routes, so you can switch models without rewriting code.

Fine-tuning and evaluation lifecycle

Manage fine-tuning jobs, datasets, evaluations, and model imports/exports in one place. Custom models and reusable skills let your intelligence compound with proprietary knowledge and feedback loops.

Governance and policy-as-code

Enforce guardrails, AGT YAML policies, fallback rules, and credential sources across all AI activity. Role-based access, per-key budgets, and rate limits keep production safe and auditable.

Agent and tool integrations

Connect coding agents like Cline, Roo, Continue.dev, and Aider, plus IDEs like Cursor, VS Code, and Windsurf. MCP servers and resource catalogs make agents, tools, and skills discoverable and governable.

What stands out

Tuning Engines helps teams build sovereign AI systems where models compound with proprietary knowledge, not just generic API calls.

This isn't just another model router or fine-tuning dashboard. Tuning Engines is a full operating layer that unifies inference, governance, and agent workflows under one roof. The combination of policy-as-code, tenant isolation, and coding-agent integrations means you can move from prototype to regulated production without stitching together a dozen tools. Teams get cost-aware routing, audit trails, and the ability to let models learn from business rules and feedback loops—all while keeping intelligence inside your own stack.

Worth checking out if…

You're building production AI systems that need to balance model flexibility with governance, cost control, and team collaboration. If you're tired of managing separate tools for inference, fine-tuning, evaluations, and agent access—or if you need to enforce policies across multiple models and coding workflows—Tuning Engines gives you a single, sovereign platform to operate at scale.