AxWise Flow is built as a highly structured, self-contained Python package. Run the pip installation command to configure local SQLite/Postgres pgvector grounding databases, or use the 1-click Docker setup to deploy instantly:

Triggers a closed-loop E2E cognitive simulation. Leverages normal Gaussian distributions matching the corporate hierarchy of specific occupations to generate grounded psychographic OCEAN twin vectors.

import requests

url = "http://localhost:8000/api/simulate-enhanced"
payload = {
    "occupation": "CFO",
    "seniority_years": 15,
    "regulatory_framework": "BaFin-MaRisk"
}
response = requests.post(url, json=payload)

{
  "status": "success",
  "evaluated_age": 45.2,
  "traits": {
    "Conscientiousness": 0.93,
    "Agreeableness": 0.33
  },
  "compliance_flags": ["BAFIN-LOG-OK"]
}

Maintains deterministic evidence mappings by linking goals, workflows, and problems back to exact character index offset boundaries in raw user transcripts, fuzzy-correcting speech typos.

import requests

url = "http://localhost:8000/api/parse-evidence"
payload = {
    "raw_transcript": "Lukas: Honestly, it's a completely manual mess. We use Excel spreadsheets..."
}
response = requests.post(url, json=payload)

{
  "status": "resolved",
  "evidence_mappings": [
    {
      "key": "pain_points.sheets",
      "phrase": "maintaining 45 spreadsheets",
      "start_char": 150,
      "end_char": 236
    }
  ]
}

Validates developer identity credentials and clearance levels before injecting sensitive corporate documents to digital twins. Secures system boundaries against malicious context prompt injections.

import requests

url = "http://localhost:8000/api/query-vault"
headers = {"Authorization": "Bearer dev_token_xyz"}
payload = {
    "resource": "finance/salary_ledger_2026.xlsx"
}
response = requests.post(url, headers=headers, json=payload)

{
  "status": "denied",
  "user": "marcus_chen_dev",
  "error": "Insufficient privileges. Required role: CFO",
  "audit_trail_block": "0x42f88b"
}