Graded B on resilience. In Vannus's assessment it has not disclosed which model it runs — resilient — owns model IP or routes across providers.
AI document analysis and research platform aimed at finance — asset management, private equity, investment banking — running structured queries across large document sets (filings, diligence rooms, credit agreements) with cited answers. The vendor states it "never trains on your data" and that data is "encrypted at rest with AES 256 and in transit with TLS 1.3". No legal entity, headquarters count
Not disclosed. Hebbia does not publish which model it runs, so this criterion is excluded and the grade rests on what we could verify. We say so rather than guess.
This is a separate question from the grade above. The grade measures resilience — whether the tool endures and whether you could leave it. This measures who can compel your data. A tool can score modestly on one and strongly on the other, and many do.
The vendor's published or catalog-recorded posture — the concrete facts this grade is built from. A full audit verifies each against the vendor's current documentation.
Vannus grades Hebbia against nine dimensions of trust — 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 →