Internal Knowledge Assistant Tailored to Each Employee

Scenario

Internal “Ask AI” for company docs/code/processes that needs to adapt to each employee’s role and knowledge level.

Extraction

From questions, docs visited, and tools used, GetProfile creates:

department, team, role
project_contexts[]: which repos / services they touch
topic_familiarity: “deep in payments service”, “novice in infra”, etc.
documentation_style_preference: likes code samples vs concept docs

All inferred from their questions and link click patterns.

Injection

When they ask, “How do I add a new metric to our billing pipeline?”:

GetProfile injects:
- “User is on the billing team, familiar with service X but not Y; prefers answers with code snippets and direct links to runbooks.”
Plus a couple of relevant memories:
- previous similar question and answer,
- docs they read last time.

Impact

The assistant answers at the right depth and with the right references.
Onboarding is smoother, since the assistant adapts to each newcomer over time.

Implementation

import OpenAI from 'openai';

const client = new OpenAI({
apiKey: process.env.GETPROFILE_API_KEY,
baseURL: 'https://api.yourserver.com/v1',
defaultHeaders: {
'X-GetProfile-Id': employeeId,
'X-Upstream-Key': process.env.OPENAI_API_KEY,
},
});

// Knowledge base query
const response = await client.chat.completions.create({
model: 'gpt-5',
messages: [
{
role: 'system',
content: 'You are an internal knowledge assistant. Provide answers at the appropriate depth for the employee\'s role and expertise.',
},
{
role: 'user',
content: 'How do I add a new metric to our billing pipeline?',
},
],
});
// GetProfile injects employee's role, expertise areas, and documentation preferences

Trait Schema Example

{
  "department": {
    "type": "string",
    "description": "Employee's department"
  },
  "team": {
    "type": "string",
    "description": "Employee's team"
  },
  "role": {
    "type": "string",
    "description": "Job title or role"
  },
  "project_contexts": {
    "type": "array",
    "items": {
      "type": "string"
    },
    "description": "Repositories, services, or projects the employee works on"
  },
  "topic_familiarity": {
    "type": "object",
    "description": "Familiarity level per topic or service",
    "additionalProperties": {
      "type": "string",
      "enum": ["novice", "intermediate", "expert"]
    }
  },
  "documentation_style_preference": {
    "type": "string",
    "enum": ["code-samples", "concept-docs", "step-by-step", "reference"],
    "description": "Preferred documentation format"
  }
}

Proxy Integration

Set up automatic context injection for your knowledge base

Memories API

Store and retrieve past questions and answers

​Scenario

​Extraction

​Injection

​Impact

​Implementation

​Trait Schema Example

​Related Resources