ScrapeGraphAI
Vannus records that this vendor routes across several model providers — not captured by one. Every finding below is quoted to the vendor’s own document, or marked not disclosed where the vendor publishes nothing.
Open-source Python library using LLMs and graph logic to build AI-driven scraping pipelines for websites and local documents (HTML/JSON/MD/XML)
It is possible to use different LLM through APIs, such as OpenAI, Groq, Azure, Gemini, MiniMax and more, or local models using Ollama.
Training and retention posture varies by plan. What we publish above describes the vendor’s default plan; enterprise, team and API agreements frequently differ, often materially, and a contract can override the published default entirely. Check your own plan and contract before relying on this row.
This is a separate question from the grade above. The grade measures resilience — whether the tool endures and whether you could leave it. This describes who controls the vendor. A tool can score modestly on one and strongly on the other, and many do.
On U.S. CLOUD Act reach specifically: the statute reaches a provider subject to U.S. jurisdiction over data in its possession, custody or control. Corporate control is a strong indicator of that and it is what we can evidence from published documents — but it is not the whole test. A company founded outside the U.S. can still contract through a U.S. entity or run substantial U.S. operations. Treat this as a starting point for your own review, not a legal determination, and take advice on anything that matters.
Vannus publishes a nine-dimension trust framework — data sovereignty, training privacy, compliance posture, operational resilience, exit portability, and more. The heaviest criterion asks whether the tool builds its own AI or resells someone else's model; where the vendor discloses it, the grade cites the vendor's own documentation. No paid placements — scoring is walled off from affiliate revenue. See the methodology →