Fuel iX™ Platform

Manage, monitor and integrate all of your GenAI capabilities

Our model-neutral platform orchestrates interactions between 100+ LLMs and GenAI applications through a secure, unified control plane.

  • Scalable performance

A central integration hub that connects your AI models and third-party apps seamlessly. Eliminate the complexity of isolated experiments and transition instantly to a robust, enterprise-wide AI infrastructure that grows with your business.

  • Governance and brand safety

Centralized moderation and guardrails provide a single control plane for all AI activity, ensuring every model interaction remains compliant, accurate and aligned with rigorous corporate safety and ethical standards.

  • Operational flexibility

A model-neutral and cloud-neutral platform provides the freedom to switch between over 100 leading LLMs and multiple cloud providers at any time, preventing lock-in and ensuring your infrastructure stays at the cutting edge of AI evolution.

Fuel iX Platform: Connect, observe and control your GenAI

Stop patching together fragmented tools that invite security leaks, sky-high API bills and hallucinations that could dismantle your brand’s reputation in seconds.

  • Centralized GenAI control plane
    Unify your AI apps, models and tools in one interface. The Fuel iX platform provides the backbone to orchestrate workflows and monitor performance across the enterprise.

  • Model arbitration & orchestration
    Smartly route requests and manage interactions between AI models, data sources and third-party apps. Our integration server ensures your GenAI stack works as a cohesive, high-performance system.

  • Enterprise-grade moderation & safety
    Implement real-time validation and guardrails to stop hallucinations and ensure brand-safe outputs. Protect your organization with automated moderation that filters content at the platform level.

  • Full-stack observability
    Gain total visibility into your AI operations. Monitor performance, track model usage and audit interactions across all applications to ensure accountability and optimize your AI investments.

  • Certified "Privacy by Design" foundation
    Build on the first ISO 31700-1 certified GenAI platform. The Fuel iX platform ensures every app inherits enterprise-grade encryption, data sovereignty and secure identity management.

Award-winning GenAI

Fuel iX enables production-grade generative AI for the enterprise. TELUS received the first Privacy by Design certification (ISO 31700-1) for its GenAI-powered customer support chatbot, built on Fuel iX.

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Frequently asked questions

  • What is the difference between an AI platform and an AI application?
    An AI application is a tool built to perform a specific function (e.g. a customer service chatbot, a document summarization tool, a code assistant). An AI platform is the underlying infrastructure those applications are built on and run through. It provides the model arbitration and orchestration, moderation and safety controls, full-stack observability and integration capabilities that individual applications rely on but don't manage themselves. The distinction matters for enterprises because buying or building AI applications without a platform means each one operates in isolation, with its own model connections, its own security configuration and no shared visibility across them. A platform is what makes it possible to scale from one AI application to many while keeping every interaction governed by the same controls. The Fuel iX Platform is a model-neutral and cloud-neutral foundation for enterprise GenAI, giving organizations a single control plane for the applications, models, and workflows running across their business.

  • What is LLM orchestration and why does it matter for enterprise AI?
    LLM orchestration is the control layer that coordinates how requests are routed, governed and responded to across one or more large language models in an enterprise environment. Rather than connecting applications directly to individual models, a model-neutral orchestration layer sits between them, handling model arbitration, prompt management, fallback logic, moderation and observability through a single interface. For enterprises running multiple AI applications across departments, this matters because it replaces the fragmentation of every team managing its own model connections, which creates inconsistent governance, unpredictable costs and infrastructure that breaks every time a model is updated or replaced. A unified control plane lets the GenAI stack work as a cohesive system.

  • How does a centralized AI control plane reduce enterprise security risk?
    A centralized AI control plane is the layer where enterprise security policies, access controls and guardrails are enforced consistently across every model interaction, regardless of which application or team is making the request. Without it, AI security is only as strong as the weakest individual integration, and the most common enterprise risks (shadow AI usage, prompt injection, data leakage to external models and inconsistent policy enforcement) all stem from the same root cause: fragmented infrastructure where every application implements its own controls. A control plane addresses this by making policy violations and unusual usage patterns visible at the infrastructure level rather than buried inside individual applications, and by giving builders ready-made security controls so they don't have to build authentication, guardrails and logging into every application themselves. For regulated industries, it also produces a unified audit trail, simplifying evidence generation for frameworks like the EU AI Act, ISO 42001 and GDPR. The Fuel iX Platform provides this control plane for enterprise GenAI, ensuring every model interaction passes through the same security and compliance controls regardless of where in the organization it originates.

  • What is an AI gateway and what role does it play in enterprise AI infrastructure?
    An AI gateway is the access and policy enforcement layer that sits between enterprise applications and the AI models they connect to. It handles authentication, rate limiting, usage tracking, cost governance and policy enforcement in one place, so every model interaction passes through the same security and compliance controls regardless of which application, team or model provider is involved. In a model-neutral platform like Fuel iX, the gateway works alongside the orchestration layer: orchestration decides how requests are routed and arbitrated across the LLMs an enterprise chooses to use (Fuel iX supports 100+), and the gateway enforces the access, usage and compliance policies that govern those requests. Together they prevent ungoverned AI access, control costs and give enterprises a single auditable checkpoint for every interaction with every model.

  • How do enterprises monitor and observe LLM performance in production?
    Enterprises monitor LLM performance in production through observability across three dimensions: what the model is doing, how well it is doing it and what it is costing. In practice, this means tracking inputs and outputs to detect hallucinations, policy violations and unexpected behavior; measuring latency, error rates and response consistency across providers; and monitoring token consumption and API costs against usage patterns. Observability works alongside guardrails, which filter inputs and outputs in real time, to give enterprises both prevention and detection: guardrails stop policy violations before they reach users, and observability records what's happening across every model interaction so teams can spot patterns, drift and emerging risks. Without a centralized observability layer, enterprises typically discover performance issues through user complaints or billing surprises rather than proactive monitoring. The Fuel iX Platform provides full-stack observability across all connected models and applications, with auditable records of every interaction so issues are caught at the infrastructure level before they reach end users.

  • How do model-neutral and cloud-neutral AI platforms future-proof enterprise AI investments?
    A model-neutral and cloud-neutral platform decouples the application layer from the model layer, so organizations can adopt new models, switch providers or run different models for different use cases (a fast inexpensive model for one task, a frontier model for another) without rebuilding their AI infrastructure. This matters because the AI model landscape changes faster than most enterprise infrastructure: models that lead on performance today are routinely displaced within months, and pricing structures shift with little notice. Enterprises that build directly on a single provider, or a single cloud, inherit all of that volatility. Future-proofing enterprise AI means putting investment into the applications and workflows built on top, rather than into constantly adapting to whatever a single provider decides to do next. The Fuel iX Platform is model-neutral and cloud-neutral by design, supporting 100+ LLMs across multiple cloud providers, with the model arbitration, orchestration and full-stack observability needed to operate them as a unified system.

  • How does the Fuel iX Platform integrate with existing enterprise tools and infrastructure?
    The Fuel iX Platform integrates with existing enterprise infrastructure through a standard API layer, so AI capabilities can be embedded into the applications and workflows teams already use without requiring them to change how they work. This covers integration with third-party software, existing data sources and the LLMs an enterprise chooses to use (Fuel iX supports 100+) across multiple cloud environments. For enterprises with existing AI investments, the platform acts as a unifying layer rather than a replacement, centralizing model arbitration, moderation and safety, and full-stack observability across applications that may have been deployed independently.

  • How do enterprises track and control AI API costs across multiple LLM providers?
    AI API costs accumulate quickly when multiple teams are connecting to multiple models independently, with no shared visibility into who is using what or how much. The most effective approach is routing all model interactions through a centralized control plane with full-stack observability that tracks token consumption, usage patterns and cost per model, per application and per team in real time. This gives IT and finance teams the visibility to identify where spend is concentrated, set usage limits before budgets are exceeded and use model arbitration to match the right model to each task based on cost and performance together. Without that centralized layer, cost management typically happens after the fact through billing reconciliation rather than proactive control. The Fuel iX Platform provides this control plane for enterprises running GenAI at scale, with the same cost and usage data forming the foundation for measuring the return enterprises are getting on their AI investments across applications and teams.