Point solutions can accelerate individual use cases, but they rarely create an enduring organisational capability. Each new tool introduces its own data boundary, governance model, user experience, and vendor dependency.
A practical starting point
An in-house AI foundation creates reusable assets: approved knowledge, model evaluation practices, policy controls, agent patterns, and domain expertise. Every successful deployment makes the next one faster, safer, and more informed.
Building in-house does not require building every model from first principles. It means retaining architectural control and decision rights over the intelligence that matters most, while using partners and foundation models where they provide genuine leverage.