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AI Controller AI Controller

A straightforward solution for controlling AI

AI Controller enables IT administrators to centrally manage AI securely, track performance and costs, enforce compliance and generate reports without complexity. AI Controller delivers the basics required of an AI gateway product, providing the core middleware without duplicating the functionality in fast-developing LLMs and front-end applications.

Control AI Internet Interface.

A diagram that illustrates how an AI Controller manages access, logging, and control

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Control use of LLMs

AI Controller provides centralized, secure and model-agnostic API management that simplifies governance and reduces administrative overhead. With built-in privacy controls, flexible authentication, and real-time cost visibility, it helps organizations protect sensitive data, prevent unauthorized access, and avoid unexpected AI spending across teams.

Security

  • Centralized storage of encrypted API keys.
  • All data in transit protected by industry-standard security protocols (HTTPS/TLS) with all API interactions logged for audits.
  • Role-Based Access Control (RBAC) to specific LLMs for individuals and groups.
  • Flexible authentication via bearer tokens or API keys.

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Privacy

  • On-premise and air-gapped deployment options.
  • Controlled user access to sensitive logs.

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Cost

  • Daily use metrics and cost tracking across all LLM AI providers.
  • Rights for individuals and teams to access LLMs aligned to AI budgets.
  • Response caching system to minimize redundant API calls.

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Control deployment and data storage

Your AI gateway, set up your way. AI Controller gives IT administration full control over how and where AI runs. Its flexible, low-overhead and future-ready architecture integrates seamlessly into existing infrastructure. AI Controller minimises setup complexity, shields sensitive data, and scales predictably as adoption grows, offering confidence from day one.

Deploy

  • Application installed on your own infrastructure (cloud, on-premise or air-gapped).
  • Standard packages for Windows, Linux and containerized deployments in Docker.
  • Minimal system requirements (4 CPU cores, 8GB RAM and 10GB disk).
  • Maintained LLM connection pooling to LLM endpoints.
  • Bearer token or API key authentication options.

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Store

  • Database located on your own infrastructure (cloud, on-premise or air-gapped).
  • All query and response content and metadata logged in the database.
  • Unified RBAC and API keys storage.
  • Built-in API query access to stored logs.

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Scale

  • No limits on how many LLMs are connected or how much data is logged.
  • Predictable scaling of compute requirements as request volume grows.
  • Dynamic LLM configuration with hot-reload capability.
  • OpenAI-compatible REST API endpoints.

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Control analysis and efficiency of LLMs

Gain deep visibility without sacrificing performance. AI Controller delivers rich, structured insights into LLM interactions with minimal overhead, enabling IT administrators to optimize use while maintaining full observability. It supports data-driven decisions and fine-tuning, ensuring fast, reliable access to AI without compromising compliance or monitoring.

Monitor and Report

  • Minimal latency overhead (<200ms per endpoint request).
  • Live dashboard tracks traffic peaks and use trends.
  • All query content and metadata logged by individual and/or team.
  • Endpoint latency, downtime and failure rates monitored by individual and/or team.

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Optimise

  • Asynchronous request processing and non-blocking architecture.
  • Direct API access to LLM endpoints without web UIs.
  • Local caching and retrieval of previously generated LLM responses.

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Ready to Take Control?

AI Controller simplifies AI adoption, management and scalability in your organisation, securely and efficiently. Whether it is governance, performance, or cost control, AI Controller gives you full command of your AI infrastructure from day one.

Try it free for 30 days and experience how straightforward and powerful secure AI management can be.

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Got questions?

AI Controller is always hosted on your own infrastructure (cloud, on-premise or air-gapped). Therefore all data stays within your environment, giving you full control and auditability.

Most teams can get AI Controller up and running in under an hour. No complicated configurations or vendor lock-ins.

Yes. AI Controller works as middleware between your current applications and LLM providers, so there’s no need to replace your existing AI tools. It offers an OpenAI-compatible REST API, supports JSON-formatted requests/responses, and includes an extensible API for seamless integration with internal systems, giving you centralized control, visibility, and security without disrupting existing workflows.

Configuration changes require AI Controller to be re-started. However, all AI Controller administration tasks (such as creation / update / deletion of Providers, Rules, Users etc.) can be performed live and do not require restarting. 

AI Controller is deployed on your infrastructure (cloud, on-premise or air-gapped) ensuring all data remains in your control. Sensitive data stored in the database, such as API Keys or passwords, is stored as a SHA512 hash and the original value is not accessible, while LLM API Keys are AES-256 encrypted.

Through local response caching, connection pooling, and asynchronous request processing, AI Controller minimizes LLM response times.

Some providers have a chat UI (e.g. ChatGPT, Microsoft Copilot, Google Gemini or Anthropic Copilot) locked to their LLMs (e.g. GPT-4, Gemini or Claude). This can prevent the use of AI gateway tools as API proxies. It is simple to configure alternate chat UIs (e.g. LibreChat) to access these LLMs.

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If you have other questions, please contact us.