autonitia-intel

Turn any business website into a clean, structured company profile — and a quick read on where the opportunities are.

Point it at a URL and get back the company's details (description, services, contact info, social presence) plus the tools and capabilities its site exposes. It also tells you how many opportunities a given lens (automation, marketing, sales…) would surface.

Want the full intelligence? The hosted Autonitia Intel API turns these profiles into verified signals, fit/opportunity scores, live industry research, and account briefings. See pricing →

Install

pip install autonitia-intel
playwright install chromium      # only needed for JavaScript-heavy sites
export OPENAI_API_KEY=sk-...      # or pass api_key in the config

Use it

from autonitia_intel import ProfileGraph

config = {
    "llm": {"model": "gpt-4o-mini"},   # add "api_key": "sk-..." or use the env var
    "lens": "automation",              # automation | marketing | sales | …
    "verbose": True,
}

graph = ProfileGraph(source="https://example.com", config=config)
result = graph.run()

print(result.model_dump_json(indent=2))

Prefer the command line?

python run.py https://example.com --lens marketing --json

What you get

{
  "target_company": {
    "name": "Example Co",
    "industry": "Real Estate",
    "description": "...",
    "location": "Dubai, UAE",
    "contact": { "phones": ["..."], "emails": ["..."], "addresses": ["..."] }
  },
  "digital_presence": { "social_media": { "linkedin": "...", "instagram": "..." } },
  "capabilities_present": ["phone", "whatsapp", "online_booking"],
  "pro_features": { "lens": "automation", "opportunities_found": 2 }
}

How it works

It fetches the site politely (respecting robots.txt, with retries and a real-browser fallback for JS-heavy pages), uses one LLM call to read out the company profile, and runs fast local checks to spot the tools and capabilities present. The opportunity count for a lens is computed locally — no guessing.

Lenses

A lens is the perspective you analyse a site through — automation, marketing, sales, and more. Lenses and the signals they look for are defined as simple YAML packs in autonitia_intel/signal_packs/, so you can add a new lens or industry pack without touching the Python.

Contributing

Contributions welcome — the easiest place to start is a signal pack: drop a YAML file under signal_packs/lenses/ or signal_packs/industries/ and open a PR. Run the tests with pytest -m "not integration".

Hosted version

This open-source engine gives you the profile and the opportunity count. The hosted Autonitia Intel turns those opportunities into verified, ranked, outreach-ready intelligence over a REST API.

→ Docs & access: autonitia.ai/intel

License

MIT — see LICENSE.