CUSTOMER ACCOUNT / ATTRIBUTED EVIDENCE
What this case establishes
This is a commercial publisher’s customer account. Roseram checked the source and wrote the analysis; it did not interview the customer, run the product, audit the figures or establish that AI caused the reported business result. The pilot below is a proposal, not a completed experiment.
Primary material reviewed 2026-10-12. Analysis and proposed evaluation by Roseram Editorial.- 01Defined question
- 02Document evidence and conflicts
- 03Reviewed analytical artifact
Hebbia: the documented workflow
Anthropic describes Hebbia applying Claude to complex document analysis for knowledge workers, including finance and legal settings. It discusses model selection and prompt generation. Reported scale and efficiency claims are attributed to the publisher/customer; this case does not verify investment conclusions or recommend acting on an AI-generated financial analysis.
The mechanism worth examining
A question across many documents may require comparing definitions, dates and exceptions rather than retrieving one paragraph. The assistant needs to know which files were inspected and which were absent. Treat every conclusion as a chain from source to interpretation. A citation trail is helpful when the exact passage supports the claim, but it cannot rescue an answer that omitted a contradictory document.
The implementation decision
Use public or synthetic documents for a pilot and define the question before loading them. Include a document that changes an earlier assumption. Require the answer to distinguish directly stated facts from derived comparisons. A useful system should reveal coverage and uncertainty in the final artifact, especially where a missing record prevents a conclusion.
Where the workflow can fail
A retrieval system may select the most semantically similar paragraph while missing a small exception elsewhere. It may also combine figures from different dates or units. Ask for a reconciliation table and a list of unresolved conflicts. Do not let a polished synthesis become a recommendation to buy, lend or transact without the appropriate human process.
A practical evaluation, designed for this use case
Create a controlled packet with known facts, one conflict and one missing answer. Compare extracted evidence with a human reference, then review the derived interpretation separately. Measure missed exceptions and time to a supported answer. This is a document-workflow test, not a simulation proving financial returns or legal correctness.
Primary sources
Figures and product details above are dated and attributed; they are not current guarantees.
- Anthropic: Hebbia primary account ↗The attributed workflow and reported result. Proposed pilots and decisions below are original Roseram analysis.
The decision matrix
Original evaluation criteria for this workflow. These are questions to test, not results measured by Roseram.
| Decision | Evidence to collect | Stop or revise when |
|---|---|---|
| Coverage | Inspected and missing files listed | Retrieved excerpts imply full coverage |
| Comparison | Dates and units reconciled | Different periods are silently combined |
| Authority | Human reviews consequential conclusions | Synthesis is treated as an investment decision |
YOUR EVALUATION / NOT A REPORTED RESULT
A small pilot you can inspect
Use these steps as a planning checklist. Checking a box records your progress in this view; it does not run or validate an experiment.
Questions this case answers
Do citations guarantee a correct answer?
No. They must support the exact claim and the analysis must account for relevant contradictory evidence.
Why include a missing answer?
It tests whether the assistant can say the documents do not establish a conclusion.
Tools & capabilities referenced
Operators studying this story often evaluate adjacent AI products. Explore Roseram guides where available:
PRACTICAL NEXT STEPS
Take the evidence into your own project.
Calculate the whole project cost
Compare subscriptions, usage, launch work and renewals.
Test an existing-project workflow
Check import, source loading, preview and publication.
Verify the output you buy
Require evidence tied to a real customer task.
Wiki brief
Hebbia is examined here for cross-document analysis with inspectable evidence. The article answers “How can an AI analyst answer questions that span many documents?” using linked primary material and original evaluation design. It is not a customer testimonial for Roseram or an endorsement by Hebbia.
Operator takeaways
- Expose coverage.
- Reconcile units and dates.
- Separate extraction from judgment.
Related case studies
Plan → build → review with routed models and transparent usage.