Arvya vs Hebbia
Hebbia reasons over documents to produce research. Arvya builds a Deal Brain from your firm's live work and prepares the next action for approval.
What Hebbia is
Hebbia (Matrix) is a document reasoning and research platform. It runs queries across very large document sets, including deal memos, data rooms, and filings, then returns synthesized, cited answers and research deliverables. It is excellent when the job is reading and making sense of a corpus.
What Arvya is
Arvya is the Deal Brain. It builds cited firm memory from live work: email, meetings, CRM, trackers, documents, research, relationship history, and data rooms. Then it turns that memory into actions the team can approve, such as tracker updates, follow-ups, briefs, CRM updates, and deal Q&A. The output is durable firm memory, not a one-off research memo.
Where each is stronger
Hebbia is stronger at
- • Deep reasoning across massive document sets in a single query
- • Research-deliverable generation over a fixed corpus
- • Scale and funding for large enterprise document workloads
Arvya is stronger at
- • Memory built from live, multi-source deal activity, not just documents
- • Prepared actions with human approval, not only answers
- • Runs inside your own Microsoft Azure tenant; raw email/transcripts never stored
Arvya vs Hebbia: FAQ
How is Arvya different from Hebbia?
Hebbia is a document Q&A and research platform that reasons over large document sets to produce answers and deliverables. Arvya builds a Deal Brain from live work across email, meetings, CRM, trackers, documents, research, relationship history, and data rooms, then turns that memory into work the team can approve. Hebbia helps you read a corpus; Arvya helps the firm remember and act.
Is Arvya a document Q&A tool like Hebbia?
No. Document Q&A is one capability inside Arvya, but Arvya's product is the Deal Brain: a cited memory of the whole deal that prepares work across the deal lifecycle.
Can Arvya answer questions over a data room like Hebbia?
Arvya can answer scoped deal and diligence questions with cited sources from the live deal context, including data-room activity. Its emphasis is connecting that context into ongoing firm memory and reviewable actions, rather than one-off research over a static corpus.