SelfHosted LLM Gateway: Manage Your AI Costs and Usage in a Single, Secure, and Zero-Maintenance Place using Google Antigravity and Neural Language Skills

As enterprise AI budgets balloon, organizations face a critical dilemma: how to maintain absolute control over AI costs, billing quotas, and data security without taking on the massive overhead of building and maintaining custom gateway infrastructure.

Usually, companies are forced to choose between two undesirable options:

1. Commercial SaaS Middleware: Paying markup fees and routing sensitive corporate data through third-party routers.
2. Heavy Custom Engineering: Tasking a dedicated software engineering team to write, host, and maintain a custom proxy server to handle API keys, load-balancing, and streaming failovers.

Today, there is a third, sovereign path.

By leveraging Google Antigravity — an advanced agentic coding assistant — and using only natural language instruction (neural language skills), any organization can build, deploy, and maintain SelfHosted LLM Gateway. This local, secure gateway unifies all AI providers in a single place with zero middleman subscription costs and zero manual coding maintenance.

Here is the blueprint for how AI-agent programming enables sovereign enterprise AI orchestration.

The Core Concept: Sovereign AI, Managed in Plain English

The fundamental shift is simple: We no longer need to write code to maintain our software infrastructure.

When building TV LLM Gateway, I did not write backend route handlers, build React dashboard layouts, or manually parse streaming chunk bytes from Gemini, Claude, or OpenAI.

Instead, I used neural language skills — instructing Google Antigravity in plain English to build a unified proxy. The agent handled:

• Creating a robust, file-based database for keys and rules.
• Writing a translations engine that maps standard OpenAI payloads onto Gemini and Anthropic.
• Creating a high-fidelity glassmorphic dashboard with native SVG charts for real-time latency and spend auditing.
• Programmatically running verification scripts to test fallback cascades.

When your code is generated, verified, and updated by an agentic assistant, maintenance drops to zero. If a provider updates their API or you want to add semantic caching, you don’t open an editor; you simply tell Google Antigravity what you need, and the gateway is updated securely in seconds.

One Control Room: Cost, Usage, and Resiliency in One Secure Place

TV LLM Gateway groups all your generative AI connections into a single local console, delivering enterprise-grade capabilities:

1. Centralized Key & Usage Auditing

Instead of dispersing API keys across multiple microservices (which invites key leaks and billing surprises), all credentials for OpenAI, Gemini, and Claude are configured and stored in a single, secure, local environment. The dashboard computes exact input/output tokens, captures latency, and tracks aggregated costs for every single API call — providing clear observability of total requests, success rates, average latency, and costs down to four decimal places.

TV LLM Gateway Dashboard Console UI

2. Visual Model Routing & Credentials Management

Through the Model Router Settings page, developers can seamlessly add provider API keys (OpenAI, Anthropic Claude, Gemini) and enable/disable them instantly. You can also configure virtual gateway models (like the Smart Router or Fast Router) with custom fallback rules, directing traffic dynamically based on availability and performance.

TV LLM Gateway Model Router Configuration Panel

3. Real-Time Request Logging & Debugging

Every LLM call leaves a precise audit trail. The Request Logs table shows timestamps, routes, specific models utilized (such as gpt-4o-mini, claude-3-5-sonnet, or gemini-1.5-flash), response latency, token consumption details, and request status (such as 200 OK or ERROR). This level of transparency makes debugging billing anomalies and failovers effortless.

TV LLM Gateway Request Logs Table View

4. Interactive Playground Sandbox

The built-in Chat Playground allows live testing of virtual models, routing policies, and fallback logic in a secure sandbox. You can toggle Server-Sent Events (SSE) streaming responses, tweak temperature values, configure maximum token limits, and view live session metrics directly as you chat.

TV LLM Gateway Chat Playground Sandbox

5. Whitespace & Scope Sanitization

Using API keys from system environments often introduces silent failures due to hidden trailing spaces or carriage returns (\r). The gateway automatically sanitizes keys before making requests, eliminating hours of troubleshooting.

Why Agentic Orchestration is Mandatory for Future Enterprises

SaaS API gateways are a legacy model. In the era of generative intelligence, every organization will require an on-premise, secure gateway for three reasons:

1. Total Data Sovereignty

Under GDPR, HIPAA, and corporate data-privacy compliance, you cannot allow customer prompts to traverse third-party routing networks. Hosting your own TV LLM Gateway locally or inside your private corporate cloud ensures that your data remains securely within your perimeter.

2. $0 Middleware Subscription Costs

Aggregators charge monthly platform fees or markups on token volume. TV LLM Gateway runs for free, communicating directly with the official APIs using your raw billing rates.

3. Agentic Autonomy

By coupling your local gateway with an agent like Google Antigravity, your AI stack becomes self-healing. If a model endpoint deprecates or a new LLM provider emerges, you use your natural language skills to instruct the agent to update the provider clients. You get enterprise-grade flexibility without dev-ops overhead.

Conclusion: Autonomy is Just an Instruction Away

The combination of Google Antigravity and local routing architectures represents the future of corporate software. You no longer need to pay middlemen or assign expensive engineering resources to build routing dashboards.

By utilizing neural language skills, you can orchestrate your own AI engines, govern your budgets, and secure your prompts in one single place — safely, cost-effectively, and with zero manual maintenance.

Source Code — https://github.com/tiru/llm-gatway

TV LLM Gateway is fully built, tested, and running in your workspace. Open the dashboard console on http://localhost:5173/ to configure your keys and test the failovers live.