Grounded context
Also written: Grounding
AI answers based on specific, verifiable company documents, not general knowledge.
Grounded context means an AI's answers come directly from specific information you provide, like company documents. Instead of guessing or using general internet knowledge, the AI sticks to the facts in the data it's given.
For example, imagine asking an AI about your company's vacation policy. If it uses grounded context, it will look up the official policy document and tell you exactly what it says. If it doesn't use grounded context, it might give you a generic answer that's not accurate for your company.
Grounded context refers to providing an AI model with specific, verifiable information from a defined corpus or set of documents during inference. This technique, often implemented through Retrieval Augmented Generation (RAG), aims to reduce model hallucinations by forcing the AI to base its responses on the provided context rather than its parametric knowledge alone. The quality and relevance of the retrieved information directly impact the accuracy and reliability of the generated output.
Microsoft's work on enterprise connectors for Copilot highlights the growing need for AI to access and process private, specific company data reliably. This is crucial for business applications where accuracy and adherence to internal policies are paramount, moving AI beyond general knowledge to actionable insights within an organization.
- 1 million documents to 300+agents: Building an enterprise-scale Microsoft 365 Copilot connectorMicrosoft · Microsoft 365 Copilot Blog ·
- Microsoft Copilot
- Microsoft Copilot uses grounded context to access and process internal documents, enabling it to provide answers and perform tasks based on specific enterprise data.
- Fine-tuning
- Fine-tuning adapts a model's internal parameters based on new data,
- In-context learning
- In-context learning involves providing examples within the
- Parametric knowledge
- Parametric knowledge is information learned and stored wit
The concept of grounding AI responses in external data has roots in research aiming to improve factual accuracy and reduce confabulation. Techniques like Retrieval Augmented Generation (RAG) formalized this by combining retrieval systems with large language models.
Ask your AI assistant (like ChatGPT, Gemini, or Copilot) a question about a specific, niche topic you know the answer to. Then, try to provide it with a short text containing the correct answer and ask the question again, instructing it to only use the provided text. Observe if the answer changes and becomes more accurate.
The Playbook: reusable how-tos, prompts, configs and tips pulled out of the news.
- HeuristicGround Claude's outputs in your internal knowledgeProvide Claude with your specific documents, code, or data to ensure its responses align with your organizational context. · 5 min
- System promptOrganize Claude chats into Projects for focused workGroup related chats and knowledge within a Project to enhance Claude's effectiveness for specific tasks. · 5 min
- PromptRole-play a student struggling with math for AI tutor simulationSimulate a student's math struggles and uncertainty for AI tutor evaluation. · 5 min
- TemplateReusable workflow templates for healthcare teamsTeams can create and share templates for common workflows like documentation or prior authorizations. · 15 min
- TemplateTemplate for building an AI tool tailored to your workA structured approach to defining and building a custom AI tool for specific business needs. · 15 min
Questions people ask
- How does grounded context prevent AI from making things up?
- By requiring the AI to base its answers on specific documents you provide, it has a verifiable source to refer to, significantly reducing the chances of generating incorrect or fabricated information.
- Is grounded context the same as training data?
- No, grounded context is information provided to the AI at the time of the request (inference), while training data is used to build the AI model itself.
First seen on Subvolts Jul 23, 2026. Updated Sep 15, 2026. Written by an AI model from the items above and reviewed against them weekly; report an error.