Tuning Engines

Tuning Engines is a unified AI control and governance layer purpose-built for teams that are serious about moving beyond isolated experiments and into production intelligence. Think of it as the operating system for your AI stack, bringing together models, agents, tools, fine-tuned systems, and every piece of the AI lifecycle into one governed platform. It is designed for developers who want speed and flexibility, and for admins who need security, observability, and cost control.

At its core, Tuning Engines provides a single, OpenAI-compatible API endpoint that gives you instant access to over 100 models including open-weight favorites like Llama 3.3, DeepSeek V3, Qwen 2.5, and Mistral Small 3, as well as commercial frontier models and your own custom tuned variants. You keep your existing SDK, swap one base URL, and suddenly you have centralized policy, full auditability, and token controls applied to every request. It is a drop-in replacement that transforms how you manage AI.

But Tuning Engines goes much further. It covers the full model lifecycle: build, tune, and scale. You can run supervised fine-tuning and LoRA adapters on your data, host your own models without managing GPU infrastructure, and run evaluations to ship with evidence. The platform also includes guardrails, policy-as-code with AGT YAML, runtime traces, usage analytics, and team management with role-based access and per-key budgets.

What makes Tuning Engines truly stand out is its philosophy on pricing. Infrastructure costs are passed through at-cost with zero markup. You only pay for support and platform upkeep. This is a refreshingly honest approach in an industry full of hidden fees and opaque pricing. It is backed by Google Cloud for Startups, NVIDIA Inception, and other major programs, giving it serious credibility.

Tuning Engines is for anyone building production AI: from code assistance and conversational AI to agentic systems, search and retrieval, multimodal workflows, and enterprise RAG. It connects seamlessly with Claude Code, OpenCode, Aider, Cline, Continue.dev, Cursor, VS Code, Windsurf, and other AI coding workflows, making it a natural choice for teams that want one governed platform for all their AI interactions.

Unified Inference

One OpenAI-compatible endpoint for every model you need. Open models, commercial frontier models, and your own tuned variants all behind a single API. You keep your existing SDK, swap the base URL, and instantly get centralized policy, full auditability, and token controls applied to every request. No code rewrites, no new clients to learn, just a drop-in replacement that gives you access to over 100 models with streaming and structured output support.

Model Tuning

Adapt open models to your specific data, workflows, and production goals without managing GPU infrastructure. Run supervised fine-tuning and LoRA adapters so your models learn your language, your tasks, and your business logic. The platform handles the infrastructure, letting you focus on quality and iteration. Evaluation gates are built in so you can measure quality, compare variants, and ship with evidence.

Policy and Governance

Centralized guardrails, access controls, and full request traceability across every model and every interaction. Admins get role-based access, per-key budgets, rate limits, routing profiles, fallback rules, policy-as-code with AGT YAML, credential sources, and usage traces. This is the control layer that transforms AI from a wild west experiment into a secure, observable, and cost-aware production system.

Token Economics

Cost ceilings, quotas, routing policies, and fallback rules so spend and rate limits stay predictable. No more surprise bills or runaway costs. You get full visibility into usage analytics, billing controls, and tenant isolation. Combined with the at-cost infrastructure pricing, this gives you complete financial control over your AI operations.

Code Assistance

Build IDE copilots, code generation tools, refactoring agents, and debugging assistants that connect seamlessly with Claude Code, OpenCode, Aider, Cline, Continue.dev, Cursor, VS Code, and Windsurf. One governed platform for all your AI coding workflows, with centralized policy and auditability across every developer interaction.

Conversational AI

Deploy customer support bots, internal helpdesks, and multilingual chat systems that can route between models based on cost, quality, or latency requirements. Use fallback policies to ensure uptime and guardrails to keep conversations safe and compliant. All interactions are traceable and auditable.

Agentic Systems

Build multi-step reasoning, planning, and tool-using execution pipelines that leverage agents, MCP servers, and reusable skills. The platform handles model routing, fallback policies, and runtime traces so your agents can operate reliably at scale without you worrying about infrastructure or governance.

Enterprise RAG

Secure, scalable retrieval over knowledge bases and private documents with centralized policy controls. Use embeddings from the model library, route queries to the best model for your task, and keep every interaction auditable. Perfect for organizations that need to combine AI with their proprietary data while maintaining strict access controls.

How does the unified API work with my existing code?

You keep your existing OpenAI SDK. Simply change the base URL to https://api.tuningengines.com/v1 and use your Tuning Engines API key. All your existing code for chat completions, streaming, and structured output works immediately. You can call any open, commercial, or tuned model by changing the model parameter. No code rewrites, no new clients to learn.

What models are available on the platform?

Tuning Engines gives you instant access to over 100 models including open-weight favorites like Llama 3.3 70B, DeepSeek V3, DeepSeek R1, Qwen 2.5 72B, Mistral Small 3, Mixtral 8x7B, Gemma 2 27B, and Llama 3.2 Vision. You also get commercial frontier models, audio models like Whisper Large v3, and embedding models from the BGE/E5 family. Plus, any model you fine-tune with the platform is available through the same endpoint.

How does the at-cost pricing work?

Tuning Engines passes through all infrastructure costs at-cost with zero markup. You pay exactly what the infrastructure costs, plus a platform fee for support and upkeep. This is a radically transparent approach that eliminates the hidden margins common in other AI platforms. You get full visibility into your costs and complete control over your budget with cost ceilings, quotas, and routing policies.

What governance controls are available for admins?

Admins get a comprehensive set of 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 with runtime traces, usage analytics, billing controls, tenant isolation, and team management. This transforms AI from an ungoverned experiment into a secure, observable, and cost-aware production system.

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