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Scenario

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

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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.

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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.

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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.

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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

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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