AI Technology Selection

Our Platform-Agnostic Approach to AI Selection

We don’t push a single AI solution. Instead, we match technologies to your precise business goals, drawing on our partnerships with leading AI providers. Our expert consultants work with you from assessment to integration, ensuring the chosen technology not only works technically but also delivers commercially.

Our expertise spans the world’s most advanced AI platforms, including:

Key Considerations for AI Platform Selection

When advising clients, we evaluate AI technologies against a set of critical success factors:

• Data Readiness: This is where most projects succeed or fail. We audit both your structured data (databases, transactions, clean datasets) and unstructured content (documents, emails, images, audio). The quality, volume, and accessibility of your data will determine which AI approaches are even possible.
• Scalability: A pilot project that works for 100 users might crash and burn at 10,000 users. We model your growth scenarios and stress-test platforms against realistic usage patterns. This includes both computational scaling and cost scaling – some solutions that seem affordable quickly become expensive as you grow.
• Integration Capability: Your new AI system needs to talk to your existing software, databases, and workflows. We map these dependencies early because integration problems can be expensive to fix later. Some platforms play well with legacy systems; others require significant architectural changes.
• Security and Compliance: GDPR, CCPA, HIPAA, and industry-specific regulations aren’t optional extras. We ensure your chosen platform can handle your compliance requirements without compromising functionality. This includes data residency, encryption standards, access controls, and audit capabilities.
• Customisation and Flexibility: Off-the-shelf solutions work for some use cases, but many businesses need models that understand their specific terminology, processes, or industry context. We evaluate how easy it is to fine-tune models, integrate proprietary data, and maintain custom configurations over time.
• User Accessibility: The most technically impressive AI system is worthless if people won’t use it. We consider the learning curve for both technical and non-technical users, the quality of interfaces and documentation, and how well the system fits into existing workflows.