Tuning Engines

Tuning Engines is a revolutionary unified AI control and governance layer, engineered by CerebrixOS, for teams building production intelligence across models, agents, tools, and fine-tuned systems. It functions as a universal intelligence runtime that allows organizations to secure, govern, and optimize every AI interaction through a single, powerful platform. Tuning Engines brings together the entire AI lifecycle—from inference and model routing to fine-tuning, evaluations, and deployment—into one governed ecosystem. Developers gain access to OpenAI-compatible APIs, Anthropic-compatible routes, CLI workflows, and MCP access, enabling seamless integration with tools like Claude Code, OpenCode, Aider, Cline, and Continue.dev. For administrators, the platform provides robust controls including role-based access, per-key budgets, rate limits, routing profiles, guardrails, policy-as-code, and full auditability. The core value proposition is moving organizations beyond isolated AI experiments into a secure, observable, cost-aware, and extensible AI operating layer where models can be trained, evaluated, routed, governed, and used by agents and tools at scale. A standout differentiator is that infrastructure costs are passed through at-cost with zero markup, meaning organizations only pay for support and platform upkeep, making it a financially revolutionary approach to enterprise AI.

Unified Inference

Access any model through a single, drop-in OpenAI-compatible endpoint. This feature allows teams to call open models, commercial frontier models, and their own tuned variants without rewriting code or learning new SDKs. Centralized policy controls, guardrails, and full request traceability are applied to every request, ensuring governance is baked into every inference call.

Model Tuning and Lifecycle Management

Adapt open models to your specific data, workflows, and production goals using supervised fine-tuning and LoRA adapters. The platform manages the entire model lifecycle from building and tuning to hosting, eliminating the need for GPU infrastructure management. Evaluation gates are built in so quality moves in lockstep with your business requirements.

Policy-as-Code and Governance

Define and enforce AGT YAML policies, guardrails, routing profiles, and fallback rules across every model and agent interaction. Administrators can implement role-based access, per-key budgets, rate limits, and credential sources, transforming AI operations from ad-hoc experiments into a fully governed, auditable, and compliant system.

Cost-Aware Token Economics

Gain unprecedented control over AI spending with cost ceilings, quotas, intelligent routing, and fallback policies. The platform provides detailed usage analytics, billing controls, and tenant isolation, ensuring that spend and rate limits remain predictable and aligned with business objectives, all while infrastructure costs are passed through at-cost.

Code Assistance and IDE Copilots

Empower development teams with AI-powered code generation, refactoring, and debugging agents. Tuning Engines connects seamlessly with Cursor, VS Code, Windsurf, and Continue.dev, providing a governed backend for coding agents. Centralized policy ensures code suggestions adhere to security and compliance standards while maintaining cost visibility.

Conversational AI and Customer Support

Deploy intelligent customer support bots and internal helpdesks that leverage the best models for each interaction. Use intelligent routing and fallback policies to ensure high-quality responses, while guardrails prevent harmful outputs. Token economics and per-key budgets keep operational costs under control across multilingual chat deployments.

Agentic Systems and Multi-Step Reasoning

Build sophisticated agentic systems that perform multi-step reasoning, planning, and tool-using execution pipelines. Tuning Engines provides MCP servers, reusable skills, and agent management, allowing agents to seamlessly call models, tools, and custom skills through a single governed platform with full runtime traceability.

Enterprise RAG and Semantic Search

Create secure, scalable retrieval-augmented generation (RAG) systems over knowledge bases and private documents. Leverage the unified API to combine embedding models with generation models, while guardrails and access controls ensure sensitive information remains protected. Usage analytics provide visibility into retrieval patterns and associated costs.

What makes Tuning Engines different from other AI platforms?

Tuning Engines is a unified AI control and governance layer that brings the entire AI lifecycle into one platform. Its revolutionary differentiator is that infrastructure costs are passed through at-cost with zero markup, so you only pay for support and platform upkeep. This, combined with centralized policy control, full auditability, and token economics, creates a financially and operationally superior approach.

Which models are available through the unified API?

The platform provides instant access to a vast model library including Llama 3.3 70B, DeepSeek V3, DeepSeek R1, Qwen 2.5 series, Mistral Small 3, Mixtral 8x7B, Gemma 2, Whisper Large v3, and embedding models. Plus, you can access commercial frontier models and any model you fine-tune with us, all through the same OpenAI-compatible endpoint.

How does the policy-as-code feature work?

Administrators define AGT YAML policies that govern every AI interaction. These policies can enforce guardrails, routing profiles, fallback rules, role-based access, per-key budgets, and rate limits. Policies are applied centrally to every request through the unified API, ensuring consistent governance across all models, agents, and tools without requiring code changes in downstream applications.

Can I connect my existing development tools and agents?

Yes, Tuning Engines is built for seamless integration. Developers can connect Claude Code, OpenCode, Aider, Cline, Roo, Continue.dev, Cursor, VS Code, Windsurf, and other AI workflows through a single governed platform. The OpenAI-compatible API means you keep your existing SDK and simply swap one base URL to gain centralized policy, auditability, and token controls.