Tatsulok as a Hebbia alternative

Hebbia's main product, Matrix, is a tabular data-grid interface that runs multi-step reasoning across large document sets, contracts, filings, financial models, and transcripts, assigning AI agents to parts of a question and citing sources along the way. It has strong adoption in financial services and large law firms. It is built for power users at large institutions and is priced accordingly, with professional seats reported in the five-figures-per-year range. If your work is heavy quantitative analysis across thousands of documents at an enterprise, Hebbia is purpose-built for that.

Tatsulok shares Hebbia's most important principle: every answer is cited to its source, so you can verify it rather than trust it blindly. The difference is focus and accessibility:

• Document-centric, not a data-grid: you ask questions in plain language and get a direct, cited answer, rather than building grid queries. • Trust and sharing built in: items carry access control and citations, so you can share a cited answer or a data room safely. • Accessible: Tatsulok is built to stand up quickly for a team, not to require enterprise procurement and white-glove onboarding.

Hebbia optimizes for deep analyst workflows at scale; Tatsulok optimizes for trustworthy, shareable answers from your documents.

Choose Tatsulok when:

• You want cited, verifiable answers from your documents without an enterprise per-seat contract. • Your team values simple, access-controlled sharing (data rooms, cited links) over a power-user data-grid. • You want to start in minutes rather than run a procurement cycle.

Choose Hebbia when you need a dedicated analyst data-grid for very large, multi-step quantitative document analysis at a large institution and can justify enterprise pricing.

Feature lists are the easy comparison and rarely the deciding one. The harder question, and the one that predicts whether a tool is safe to rely on, is how fast you can check what it tells you.

Run three tests on any candidate, this one included. First, the passage test: pick a claim in an answer and see whether the tool takes you to the exact sentence supporting it, or only to a document. Second, the silence test: ask something the underlying sources cannot answer and watch whether it says so or improvises. Third, the chain test, which matters most for multi-step analytical work: when a tool reasons across many documents, can you see which document produced each step, or only the conclusion? A confident synthesis you cannot decompose is the hardest kind of error to catch.

These are not hypothetical concerns. Stanford's benchmark of leading grounded legal-research tools measured hallucination rates between 17% and 33% even with retrieval in place, against 43% for a general model. Grounding lowers the rate substantially; it does not remove the need to look.

This week's drill, no signup needed: run the passage test once on whatever tool you use today. Take one claim that matters and time how long it takes to reach the sentence behind it. That number, more than any feature grid, is what you are really buying.

Yes. Citations are core to Tatsulok, not an add-on. Every answer links back to the exact passage in your documents, so any reader can confirm a claim against the original. This is the same trust principle Hebbia emphasizes, that the answer must be checkable, applied in a simpler, document-centric product. For high-value work where a wrong answer is costly, verifiability is the feature that matters most, and Tatsulok makes it the default.