The work around the model
A model is not a product.
Practical knowledge and best practices for bringing AI into your business.
Explore the decisions around the model: where AI can add value, how to judge quality, and what it takes to run a reliable system. We help you put those ideas into practice.
The work around the model
Three parts of one system.
Architecture
Understand how models, data, and existing software fit together to support an AI product.
For example: design a support assistant that connects to approved knowledge and order systems, with clear limits on the actions it can take.
Evaluation
Decide what good performance means and measure whether an AI product meets that standard.
For example: test a support assistant on real customer questions and verify answer accuracy before approving a model change.
Operational reliability
Keep an AI product dependable, affordable, and accountable during everyday use.
For example: monitor a support assistant’s failures, set response-time and cost limits, and route unresolved issues to a person.
Insights & best practices
All InsightsLatest thinking
Contact
Ready to put AI into practice?
Whether you’re exploring a first use case or moving a pilot into everyday use, we can support your next step. Tell us what you want to achieve and where you need help.