Labels for AI Context
AI retrieval needs steering. When the AI generates content for a training services tender, it should reach for past training responses, the training-related case studies, and the training-relevant capability statements. When it generates content for an engineering tender, it should reach for engineering material. The default of pulling from everything indiscriminately produces blended, generic drafts.
Labels for AI Context is the steering mechanism. Tag each opportunity with the labels that describe it. Sector, capability, contract type, technology, whatever taxonomy fits your business. The AI uses those labels to prioritise what it retrieves from your Response Library, Business Context, and Supporting Evidence when drafting content for that tender.
The result is more relevant drafts, less manual cleanup, and content that reads as if it was written specifically for this tender.
Labels are shared across the team. Adding a new opportunity with the right labels means everyone collaborating on it benefits from the same retrieval discipline.
