Short answer
AI grounding means connecting an AI model's answer to specific, trusted data, such as CRM records, a knowledge base or policy documents, so it responds from facts rather than from general training. Grounding is what makes CRM AI assistants and agents accurate for your business.
AI Grounding explained
Grounding can happen by inserting record data into a prompt, retrieving relevant documents (retrieval-augmented generation), or letting an agent call tools that look up live data. Salesforce grounds prompts in CRM and Data 360 data, and HubSpot Breeze grounds in Smart CRM data and your knowledge base.
If an agent gives strange answers, the cause is often stale, incomplete or conflicting source data rather than the model.
How Vantage Point helps: we identify the right data sources for each AI use case, clean them, and test that answers are grounded correctly.
Frequently asked questions
What is the difference between grounding and training?
Training changes the model itself. Grounding gives the model the right information at the moment it answers, without changing the model.
Why does my AI agent use outdated information?
Usually because the data it is grounded in is out of date or because old records are not filtered out.