AI Architecture

AI architecture services help organisations design and implement systems that safely and effectively leverage artificial intelligence and machine learning. We address the architectural challenges of AI adoption, including data pipelines, model deployment, MLOps, ethical AI considerations, and integration with existing systems.

What is AI Architecture?

AI architecture is the design of systems that support artificial intelligence and machine learning capabilities, from data collection and model training to deployment, monitoring, and governance.

Effective AI architecture enables organisations to experiment with AI, deploy models to production, and scale AI capabilities across the organisation. It includes MLOps practices that support the full lifecycle of AI models.

MLOps infrastructure and practices
Model deployment and monitoring
Data pipeline integration
Ethical AI and governance

Problems

Problems AI Architecture Addresses

Organisations adopting AI face several architectural challenges:

Model deployment complexity
Data requirements and quality
Model lifecycle management
Integration with existing systems
AI governance and ethics

Typical Outcomes

Production-Ready AI Systems

AI models deployed to production and integrated with business processes

Scalable MLOps Infrastructure

Systems and processes supporting the full lifecycle of AI models

Governed AI Adoption

Frameworks ensuring AI initiatives align with business objectives and regulatory requirements

When Organisations Need AI Architecture

AI architecture is essential when:

Adopting AI capabilities for the first time
Scaling AI initiatives across the organisation
Facing production AI deployment challenges
Establishing AI governance requirements
Responding to competitive pressure

When

How AI Architecture Relates to Other Services

Data Architecture

AI systems depend on data architecture for access to quality data for training and inference

Solution Architecture

AI capabilities are often components of larger solutions, integrating with other system components

Technology Strategy

AI architecture provides the technical foundation that enables AI capabilities outlined in technology roadmaps

Cohesive Architecture's Approach

Practical & Production-Ready

We focus on creating practical, production-ready AI systems that deliver business value. We design for both technical and organisational needs, ensuring that AI architectures support effective model development, deployment, and governance.

MLOps & Governance

We work with organisations to establish MLOps practices and infrastructure that enable teams to develop and deploy AI models effectively. We consider ethical AI and governance from the start, ensuring AI systems align with organisational values.