Platforms for deploying,
governing, and operating
AI systems in production

Best for: Multi-step workflows, automation, operational assistants, and autonomous task execution.

AI agents go beyond answering questions. They can use tools, access systems, retrieve information, and coordinate actions across multiple steps.

Agentic frameworks provide the orchestration layer needed to build systems that can reason, plan, and execute business processes. As organisations move from AI assistants to AI-powered workflows, these frameworks are becoming a critical component of modern enterprise architectures.

Best for: Forecasting, fraud detection, predictive analytics, recommendations, and advanced analytics.

Machine learning remains one of the most widely adopted forms of AI in the enterprise. These platforms provide capabilities for data preparation, model training, experimentation, validation, and deployment.

They enable organisations to transform data into predictions and insights that support better decision-making across business operations.

Best for: Production deployment, monitoring, lifecycle management, reliability, and cost optimisation.

Many AI initiatives fail not because models are ineffective, but because they cannot be operated reliably in production.

MLOps and LLMOps platforms provide the processes and tooling required to deploy, monitor, govern, and continuously improve AI systems. They help engineering teams manage model versions, automate deployments, monitor performance, detect drift, and maintain operational visibility. These platforms form the backbone of production AI environments.

Best for: Risk management, compliance, security oversight, and responsible AI adoption.

As AI becomes embedded within business processes, organisations need greater visibility and control over how AI systems are developed, deployed, and used.

Governance platforms help establish policies, monitoring, auditability, and accountability across the AI lifecycle. They allow organisations to scale AI adoption while maintaining security, compliance, and trust.