🎯 Goal
Enable the AI to understand your organization’s internal language—jargon, acronyms, proprietary tools, document types, business terms—so it can respond more accurately and contextually.
This prevents misunderstandings and lets the AI behave like a well-integrated colleague, rather than an outsider unfamiliar with your internal codes.
🧠 Why Is This Useful?
In companies, people often use:
Internal acronyms (e.g., RAP, PLN, GTR)
Proprietary tools and platforms (e.g., Tool XY, ZEKE Platform)
Shorthand phrases (e.g., “ping MCD to validate the scope”)
Domain-specific expressions
➡️ Without customization, the AI may misinterpret or ignore these terms
➡️ With customization, it can recognize and contextualize them automatically
✅ Benefits
Fewer misunderstandings in conversations with the AI
Time saved interpreting queries or refining prompts
Semantic alignment with your tools, processes, and document types
The AI understands your in-house terms like an internal team member
📌 Key Takeaway
Customizing your business language is a critical step to boosting AI precision.
It transforms the assistant from a generic responder into a true copilote embedded in your team’s culture.
⚙️ How It Works in Outmind
Outmind offers two levels of customization for integrating your company’s vocabulary:
🔐 1. Private Customization
Each user can define:
Their own preferences
Specific roles or habits
Frequently used expressions
📌 Example:
“When I mention a ‘brief’, I’m referring to a client scoping PDF. The expected format includes 3 sections: context, objectives, and resources.”
👥 2. Team or Organization-Level Customization
Admins can define a shared base of internal knowledge for the whole team.
This is where you can introduce:
Company-wide jargon
Common acronyms
Product and tool names
📌 Example team content:
“PPR” = Project Progress Report, a weekly document sent to the client
“RPF” = Resource Planning Forecast
“ZEKE” = Internal agile project management platform
“NLP-Kit” = Internal text processing engine based on spaCy and custom rules
Once configured, the AI can automatically interpret these terms in queries, prompts, conversations, or documents.
🧪 Example Interaction Before/After Customization
❌ Before Customization
Question: “Where is the latest RAP stored?”
AI: “I don’t know what ‘RAP’ refers to, could you clarify?”
✅ After Customization
AI: “The latest Project Progress Report (RAP) is available in the ACME client folder – Week 14.”