Best Practices for More Accurate, Context-Aware AI Outputs
The Knowledge feature in GReminders is designed to give your AI the context it needs to operate like your firm – not a generic model. Instead of relying on assumptions, the AI uses what you define here to generate more accurate, consistent, and tailored outputs across meeting summaries, pre-meeting briefs, Ask Anything responses, and notetaker-generated content.
At its core, this feature acts as your AI’s internal playbook. The more intentional and structured your inputs are, the more your outputs will reflect your terminology, workflows, and client experience.
Where to Find It
To access the Knowledge feature, navigate to:
Setup (top right corner) → AI Agent → Knowledge
This feature is available to all users – you do not need a Notetaker license to use it.
Understanding the Two Input Fields
The Knowledge page is split into two sections, each serving a distinct purpose.
The first field, General Organization Knowledge for AI, is your foundational context layer. As noted in the product, this is where you input company terminology, workflows, policies, communication style, and key details the AI should reference. In practice, this means defining how your firm operates so the AI can mirror that structure in its outputs.
The second field, Additional Instructions for Ask Anything and Pre Meeting Brief, is more directive. The product prompt highlights using this space to define where certain pieces of information are located. This is where you guide the AI on how to retrieve and interpret data—particularly from your CRM—so outputs are not just well-written, but also accurate and actionable.
Together, these fields define both the context (how your firm operates) and the logic (how the AI should find and use information).
How to Use the Knowledge Feature
Using this feature is simple, but the impact depends entirely on the quality of what you input.
Navigate to the Knowledge page through Setup and AI Agent. Begin by populating the General Organization Knowledge field with high-level information about your firm—how you operate, how you communicate, and how you serve clients. Then use the Additional Instructions section to guide the AI on where key data lives and how it should be interpreted. Once complete, save your changes.
While this takes only a few minutes to set up, it directly influences every AI-generated output across the platform.
When Advisors Should Use the Knowledge Feature
Advisors should leverage the Knowledge feature anytime they want AI outputs to reflect how their firm actually operates rather than defaulting to generic assumptions. This is especially important in the following scenarios:
- Defining CRM structure – Clarify where key data lives (notes, risk scores, household relationships, custom fields) so AI pulls the right information
- Standardizing terminology – Ensure firm-specific acronyms and language (FP, IPS, etc.) are used consistently in outputs
- Documenting workflows – Align summaries and briefs with your onboarding process, review cadence, and service model
- Clarifying team roles – Help AI correctly attribute responsibilities across advisors, associates, and operations
- Reinforcing service offerings – Ensure outputs reflect your firm’s planning philosophy and core services
- Controlling tone and communication style – Maintain consistency in how outputs sound (professional, concise, conversational, etc.)
- Embedding compliance guardrails – Guide language around projections, recommendations, and required disclaimers
- Structuring meeting outputs – Define what should be captured across different meeting types (discovery, review, prospect, etc.)
- Segmenting clients – Tailor outputs based on client tiers and service expectations
- Reflecting investment philosophy – Ensure recommendations and summaries align with how your firm approaches risk and portfolio construction
Final Takeaway
The Knowledge feature is not just a setup step – it is a control layer for how AI behaves within your firm.
When used effectively, it transforms outputs from generic summaries into structured, context-aware insights that align with your workflows, language, and client experience. Even a small investment in building this out properly can significantly improve accuracy, reduce manual edits, and create outputs that feel like they were produced by your team – not a system.
If your AI outputs feel inconsistent or generic, this is the first and most important place to refine.