Tuning Engines

Tuning Engines is a unified AI control and governance layer designed for teams building production intelligence across models, agents, tools, and fine-tuned systems. Developed by CerebrixOS, this platform serves as a comprehensive runtime that brings together the full AI lifecycle in one governed environment. It enables organizations to move beyond isolated AI experiments into a secure, observable, cost-aware, and extensible AI operating layer. The platform supports inference, model routing, fallback policies, fine-tuning jobs, datasets, evaluations, model imports and exports, custom models, agents, MCP servers, reusable skills, guardrails, policy-as-code, data capture, runtime traces, usage analytics, API keys, billing, team roles, and integrations. Developers benefit from OpenAI-compatible APIs, Anthropic-compatible routes, CLI workflows, MCP access, coding-agent integrations, and resource catalogs for models, agents, tools, and skills. Teams can connect popular AI workflows like Claude Code, OpenCode, Aider, Cline, Roo, Continue.dev, Cursor, VS Code, and Windsurf through a single governed platform. Admins gain production-ready controls including 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. A key differentiator is that infrastructure costs are passed through at-cost with zero markup, meaning organizations only pay for support and platform upkeep. Backed by Google Cloud for Startups, NVIDIA Inception, and other major programs, Tuning Engines provides a secure, governed, and optimized environment for every AI interaction.

Unified Inference

Access any model through one OpenAI-compatible endpoint. This feature allows developers to keep their existing SDKs and simply swap one base URL to call any open, commercial, or custom tuned model. With centralized policy, full auditability, and token controls applied to every request, teams can seamlessly integrate over 100 models including Llama, DeepSeek, Qwen, Mistral, Gemma, and commercial frontier models without code rewrites or learning new clients.

Model Tuning and Lifecycle

Adapt open models to your specific data, workflows, and production goals through supervised fine-tuning and LoRA adapters. The platform supports the full model lifecycle from building with one API endpoint to tuning with your data and scaling without managing GPU infrastructure. Evaluation gates ensure quality improves with your business needs, allowing teams to run the fastest inference and host custom models seamlessly.

Policy and Governance Controls

Centralized guardrails, access controls, and full request traceability across every model interaction. Admins can implement role-based access, per-key budgets, rate limits, routing profiles, fallback rules, guardrails, policy-as-code, credential sources, and auditability. These controls ensure that every AI interaction is secure, observable, and compliant with organizational policies, making production deployment safe and manageable.

Token Economics and Cost Management

Cost ceilings, quotas, routing, and fallbacks keep spend and rate limits predictable. The platform provides comprehensive usage analytics, billing controls, and tenant isolation so organizations can manage costs effectively. Infrastructure costs are passed through at-cost with zero markup, meaning teams only pay for platform support and upkeep. This transparent pricing model enables organizations to scale AI operations without hidden fees or unexpected expenses.

Code Assistance and IDE Copilots

Build and deploy IDE copilots, code generation tools, refactoring agents, and debugging assistants. Teams can connect popular coding environments like Cursor, VS Code, Windsurf, and Continue.dev through a single governed platform. Developers get access to OpenAI-compatible APIs, CLI workflows, and coding-agent integrations that enable rapid prototyping and mission-critical code workflows with centralized policy control and auditability.

Conversational AI and Customer Support

Create customer support bots, internal helpdesks, and multilingual chat applications powered by any combination of open or commercial models. The unified inference endpoint and fallback policies ensure reliable uptime, while guardrails and content filtering maintain brand safety. Teams can fine-tune models on domain-specific data to improve response quality and reduce hallucinations in production conversations.

Agentic Systems and Multi-Step Reasoning

Build multi-step reasoning, planning, and tool-using execution pipelines with full governance. The platform supports agents, MCP servers, reusable skills, and policy-as-code through AGT YAML policies. Teams can orchestrate complex workflows where models call tools, retrieve information, and execute actions while maintaining complete traceability, audit logs, and cost controls across every step of the reasoning chain.

Enterprise RAG and Search Retrieval

Implement secure, scalable retrieval over knowledge bases and private documents. Organizations can combine semantic search with enterprise assistants and personalized recommendations using embeddings models and fine-tuned systems. The platform provides tenant isolation, role-based access, and credential management to ensure sensitive enterprise data remains protected while enabling powerful AI-driven search and retrieval capabilities.

Infrastructure costs are passed through at-cost with zero markup. Organizations only pay for platform support and upkeep. This means there are no hidden fees or unexpected expenses on model inference and compute resources. The platform provides transparent token economics with cost ceilings, quotas, routing, and fallbacks so spend and rate limits stay predictable. For specific pricing plans and tiers, please contact the Tuning Engines team directly as detailed pricing information is not publicly listed.

What is the primary value proposition of Tuning Engines?

Tuning Engines provides a unified AI control and governance layer that brings together the full AI lifecycle in one platform. Its key differentiator is that infrastructure costs are passed through at-cost with zero markup, meaning organizations only pay for platform support and upkeep. This enables teams to move 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.

How does the unified API work with existing codebases?

The platform provides a drop-in OpenAI-compatible endpoint for every model. Developers keep their existing SDKs and simply swap one base URL to call any open, commercial, or custom tuned model. No code rewrites or new clients to learn are required. The same endpoint supports over 100 models including Llama, DeepSeek, Qwen, Mistral, Gemma, and commercial frontier models, with centralized policy, full auditability, and token controls applied to every request automatically.

What governance controls are available for administrators?

Admins get comprehensive production controls including role-based access, per-key budgets, rate limits, routing profiles, fallback rules, guardrails, policy-as-code with AGT YAML, credential sources, full auditability, usage traces, billing controls, tenant isolation, and team management. These controls ensure every AI interaction is secure, observable, and compliant with organizational policies while maintaining cost predictability through cost ceilings, quotas, and routing fallbacks.

Which AI workflows and tools can integrate with Tuning Engines?

Teams can connect popular AI workflows including Claude Code, OpenCode, Aider, Cline, Roo, Continue.dev, Cursor, VS Code, Windsurf, and other coding environments through a single governed platform. Developers get OpenAI-compatible APIs, Anthropic-compatible routes, CLI workflows, MCP access, coding-agent integrations, and resource catalogs for models, agents, tools, and skills. This enables seamless integration with existing development workflows and tools.