Generative AI is no longer a futuristic technology but a business imperative : every day we witness an acceleration in the adoption of LLMs like OpenAI, Mistral, or local and on-premise models. This wave of innovation promises to revolutionize processes, unlocking unprecedented productivity.
However, it is becoming increasingly evident that the rapid and fragmented adoption of AI in enterprise companies creates a dangerous gray area, fueling growing doubts. How can one guarantee that model outputs are always consistent and compliant with regulations? How is access to dozens of different models managed, ensuring sensitive data is not exposed to vulnerabilities? And, above all, how can control over operational costs be maintained in an infrastructure where token consumption can vary drastically?
The answer to these challenges is not to limit innovation, but to channel it. This is precisely where the AI Gateway comes into play : a centralized access point, fundamental for transforming AI usage into a scalable, secure, and governed business strategy.
Bitrock supports companies throughout their digital evolution journey, with an end-to-end approach that spans from consulting to effective implementation. A holistic vision empowered by the internal product portfolio of the Fortitude Group, which includes cutting-edge technological solutions. In this context, the Radicalbit platform is positioned as a crucial enabler for the adoption and observability of Artificial Intelligence. The Radicalbit AI Gateway is the specific component designed to be the strategic intermediary between corporate applications and AI providers, both remote and local.
AI Gateway: Core Pillars and Features
The value of the Radicalbit AI Gateway is structured around three interconnected pillars, capable of solving the major critical issues related to the use of AI applications in the enterprise context:
- Governance and security: Access control, prevention of data leaks, and guarantee of compliance.
- Monitoring and compliance: Real-time tracking of metrics, performance, and usage per user/model.
- Optimization and control of operational costs: Intelligent resource management to monitor and reduce operating expenses.
Centralized Access and Governance
The AI Gateway effectively eliminates the fragmentation that often characterizes the spontaneous adoption of AI, ensuring that user authentication and permission management are the foundation for solid corporate governance.
Managing AI models requires a control console for all key roles in an enterprise environment: system administrators, DevOps, IT Operations, and auditing teams. These figures need a clear and centralized view not only of the metrics related to model performance to ensure efficiency, but also of the status of AI services for each business unit. An effective governance system must provide complete details of the characteristics of every model in use and, crucially, allow for the timely management of anomalous events.
Finally, usage monitoring and the ability to generate reports on consumption and compliance are essential to ensure that AI adoption occurs safely, efficiently, and in compliance with current policies and regulations.
Security, Compliance, and Risk Prevention Guardrails
Security and compliance are ensured by a series of advanced functionalities, decisive for auditing and compliance teams that must monitor and control model usage. The AI Gateway proactively intervenes to prevent potential data leaks and manage the dreaded reputational risk.
Static guardrails represent the first line of defense. These allow the use of simple text matches or regular expressions to block, flag, or mask specific data in transit.
The AI Gateway also allows the implementation of PII (Personally Identifiable Information) guardrails, based on Microsoft Presidio, for the identification and anonymization of personal data. The Gateway is capable of identifying a wide range of sensitive data in Italian and English, including: tax ID, credit card number, IBAN, email, and identity documents. In addition to supporting Block & Masking, the Radicalbit AI Gateway is already set up for the addition of advanced features such as data encryption and pseudonymization.
No less important is security on outputs: LLM-based guardrails act on the semantic and contextual side of responses, ensuring that outputs are compliant and preventing the generation of unwanted content or content not aligned with corporate policies.
Maximise the reliability and efficiency of your LLM applications
Ensuring the continuity and reliability of AI is just as crucial as its security. For this reason, the Gateway incorporates advanced features for traffic and fault management, ensuring that the application never stops.
In case of a primary model failure, the AI Gateway leverages the multi-model fallback feature, automatically routing the request to an alternative model. This allows for graceful degradation, controllably reducing functionalities while guaranteeing service continuity even under fault conditions.
Finally, the Gateway manages interaction robustness through intelligent retries, which use exponential backoff to prevent backend overload, with the ability to define a configurable retry limit. Only after these policies are exhausted are errors propagated to the client in a transparent manner, maintaining system stability under stress.
Optimization and Control of Operational Costs
Cost control is essential for the sustainability and scalability of AI within the company. The Gateway does not just track spending, but provides precise tools for optimization and budget management.
Intelligent routing, based on specific logic, allows you to optimise costs and performance by directing requests to the most efficient and cost-effective model.
Intelligent caching is a fundamental feature for cost reduction. By reusing responses from external LLM models through a configurable cache with TTL (Time To Live), repeated calls are eliminated, significantly reducing the costs and latency of recurring requests.
To ensure financial predictability, the Gateway also implements precise limitation tools. Rate limiting and configurable quotas regulate the flow of requests (throttling) for users or teams, ensuring that no department exceeds its budget in terms of consumption. In parallel, token limitation acts upstream to control the volume of generated tokens, preventing excessive and unexpected expenses.
All this activity is made transparent by cost tracking, which can offer a detailed visualization of consumption at the level of a single operational route.
Enterprise Users
Security and operability in enterprise environments are guaranteed by a solid layer of multi-tenancy and observability. The AI Gateway implements granular management of users, groups, and organizations, providing robust systems for authentication, authorization, and auditing to track every activity.
This architecture is made flexible by integration with major Identity Providers (IdP), such as Keycloak, leveraging industry-standard protocols like OpenID Connect (OIDC), SAML, and OAuth 2.0.
In parallel, the gateway is intrinsically oriented towards observability thanks to advanced instrumentation for sending metrics via the OpenTelemetry standard. This standard allows for the native sending of metrics and telemetry, making the data immediately analyzable in all major monitoring and AIOps tools on the market (such as Grafana, Dynatrace, Splunk, and Datadog).
Finally, to integrate perfectly into modern Platform Engineering and DevOps flows, the AI Gateway is designed for CI/CD configuration: its configuration is serialized to versionable files, while still maintaining the possibility to operate and manage services also via dedicated APIs, ensuring automation and traceability of every modification.
Support for the OpenAI Standard
To ensure maximum agility for developers and reduce vendor lock-in, the AI Gateway offers native support for the OpenAI standard.
The Gateway is designed to be fully compatible with OpenAI APIs, allowing all libraries, tools, and frameworks that already support them to use the gateway in a completely transparent manner. This means that developers do not have to apply any patch or modify existing code. This compatibility extends to the main agent and AI development frameworks, guaranteeing “one-line” support for tools like LangChain/LangGraph, PydanticAI, and CrewAI.
The gateway supports all OpenAI-compatible models, and its continuous development is already aimed at integrating Embedding models (RAG, Semantic Search) and Multimodal LLMs (Image generation, understanding, OCR).
Conclusions
Generative AI is an unmissable opportunity for modern companies, but its full potential is unlocked only through proactive and centralized governance.
The adoption of an AI Gateway is therefore indispensable: Bitrock, thanks to the Radicalbit platform, offers the architectural solution necessary to advance AI in a secure, measurable, and sustainable way.
Are you ready to transform AI adoption into governed competitive advantage? Don’t leave innovation at the mercy of uncertainty and uncontrolled costs. Contact our experts today to discuss your AI Governance strategy and book a demo of our AI Gateway.