Endex vs Hebbia (2026)
Two citation obsessed systems are separated by one manual step, and the step is the decision. Hebbia stops at the grid. Matrix decomposes a question, sends agents through every page of every document in parallel, and fills a spreadsheet of its own where each cell carries a citation resolving to the exact page, paragraph and sentence that produced it, and any cell can be overwritten. A person carries the output into the firm's models and materials, because the platform deliberately does not act in other systems. Endex removes that step. Its agent lives inside Excel itself, builds the three statement model and the valuation in the live file, reconciles disagreeing sources, catches restatements buried in footnotes, and writes the results into cells it labels as its own. The last mile inverts between them. Hebbia leaves a re keying step its users staff, and that manual carry is also a checkpoint, the moment a person decides what enters the model. Endex eliminates the re keying, which is its pitch, and with it the checkpoint, since no approval gate is described before the agent writes and the labeled traces are inspection after the fact. The manual step one vendor declined to automate is precisely the control the other removed. The evidence gap is as wide as the design gap. Hebbia's adoption evidence is strong: more than 40 percent of the largest asset managers, a traceable trajectory, and a raw usage figure of 250 billion tokens a month that is hard to inflate. Endex names buyer categories (banks, private equity above $100 billion, multi strategy funds) and attributes its one quantified outcome to an anonymous portfolio manager. Both name the models underneath through their providers' own case studies, and both leave a scale question open: Hebbia gives no per cell confidence for a grid of thousands of answers, and Endex no measured accuracy for the arithmetic it ships.
- Your supervision model requires review before anything enters the file. The grid holds every answer with a sentence level citation, any cell can be overwritten, and a person carries results into your models, so the checkpoint survives adoption.
- Adoption evidence is your comfort. More than 40 percent of the largest asset managers, a trajectory traceable from 30 percent of the top fifty two years earlier, 250 billion tokens processed monthly, and reviewer reported savings of thirty to forty hours per deal.
- Your document sets are large, messy and not just financial. Whole document reading across spreadsheets, presentations, email chains and images, secure project workspaces, and independent fit guidance pointing at teams of five to twenty analysts doing repetitive high stakes review.
- The work is in Excel and re keying is the cost you are cutting. Three statement models, valuations, reconciliation and restatement catching happen in the live file, delivered as a model, document, deck or email without a copy paste step.
- Attribution is cell level. Labeled references mark exactly which cells the agent produced and integrated citations attribute every output to its source, built for the environment where an unmarked machine edit is hardest to detect.
- You want the chain named to the version. The provider and the specific model versions serving each workflow are published.
This comparison is published by AI FinTech Index, an independent research platform that publishes independent ratings of AI vendors for financial services. Endex and Hebbia are each graded against the same capability taxonomy, from each vendor's own public materials and the regulatory record, under the AI FinTech Index verification standard. No vendor pays for placement, and no vendor has reviewed this page. How this evidence is graded
Plain facts
| Endex | Hebbia | |
|---|---|---|
| Primary category | Capital Markets & Research AI | Capital Markets & Research AI |
| Founded | Not published | Not published |
| Headquarters | New York, New York, United States | Not published |
| Website | endex.ai | www.hebbia.com |
Side by Side
Select any grade to read the note behind it.
| Axis | E Endex |
H Hebbia |
|---|---|---|
| AI Centrality | ||
| Autonomy and Oversight Model | ||
| Model Risk Management and Transparency | ||
| Operational and Outcome Evidence | ||
| AI Safety and Data Stewardship | ||
| GLBA and Data Privacy Posture | ||
| Security Certifications and Trust Center | ||
| Regulatory Status and Licensure | ||
| AI Governance and Bias Disclosure | ||
| AI Liability and Recourse | ||
| Model Supply Chain Disclosure | ||
| Core Systems and Integration Depth | ||
| Deployment Model and Data Residency | ||
| Commercial Transparency | ||
| Institution and Segment Coverage |
Product updates
The latest logged changes from each vendor, newest first, each linked to its source.
Hebbia
-
Integration / interoperability
Hebbia now integrates with Octus through the Octus MCP Connector, which links every Octus product a firm subscribes to into Hebbia at once.
Source -
Product / capability
Hebbia's October 2026 release adds memory to Max, its agent, which stores and recalls context across conversations under user controls and an org level admin switch, version history with rollback for decks and docs made in Max, and a Microsoft Word plugin for running workflows and drafting inside Word.
Source -
Product / capability
Hebbia introduced Headless Hebbia, an API and MCP server that brings its retrieval, orchestration and analysis into firms' own applications and into assistants such as Claude and ChatGPT.
Source
The short version of each
Endex
Endex puts an agent inside Excel itself. It builds three statement models and valuations in the live file, reconciles disagreeing sources, catches restatements buried in footnotes and writes results into cells it labels as its own, with the model chain published through its provider's case study. According to the AI FinTech Index, eliminating the re keying step also eliminated the checkpoint: no approval gate is described before the agent writes, and the labeled traces are inspection after the fact. No measured accuracy exists for the arithmetic it ships, no security artifact is published, and its one quantified outcome is attributed to an anonymous portfolio manager.
Source: AI FinTech Index, 2026
Hebbia
Hebbia's Matrix decomposes a question, sends agents through every page of every document in parallel, and fills a grid where each cell's citation resolves to the exact page, paragraph and sentence. A person carries the output into the firm's models, because the platform deliberately does not act in other systems. According to the AI FinTech Index, its adoption evidence is strong: more than 40 percent of the largest asset managers and 250 billion tokens processed monthly, a figure hard to inflate. Grids of thousands of cited answers ship with no per cell confidence or sampling guidance, no aggregate extraction accuracy is published, and no security artifact is public despite government users with residency requirements.
Source: AI FinTech Index, 2026
Common questions
Is Endex better than Hebbia for financial document analysis?
One manual step separates them and the step is the decision. Hebbia stops at the grid: agents fill a spreadsheet of its own where every cell carries a citation resolving to the exact page and sentence, and a person carries the output into the firm's models. Endex removes that carry: the agent lives inside Excel, builds the model and valuation in the live file, and writes into cells it labels as its own. If you want the checkpoint, Hebbia. If you want the re keying gone, Endex, and you build the gate yourself. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified August 23, 2026. No vendor pays for placement.
What does removing the manual step actually change?
The manual carry Hebbia declined to automate is also a control: it is the moment a person decides what enters the model. Endex's pitch is eliminating that re keying, and with it goes the checkpoint, since no approval gate is described before the agent writes and the labeled cell traces are inspection after the fact. Adopting Endex means building the approval gate the design removed; adopting Hebbia means staffing the carry. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified August 23, 2026. No vendor pays for placement.
Whose adoption evidence is stronger?
Hebbia's: more than 40 percent of the largest asset managers, a traceable trajectory, and a raw usage figure of 250 billion tokens a month that is hard to inflate. Endex names buyer categories (banks, private equity above 100 billion dollars, multi strategy funds) and attributes its one quantified outcome to an anonymous portfolio manager. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified August 23, 2026. No vendor pays for placement.
Do Endex and Hebbia name the models underneath?
Both do, because their providers published case studies as marketing, so the model layer is disclosed at each. What neither states is what those providers retain from confidential deal material, and neither shows a security artifact an outside buyer can verify, a gap that matters at Hebbia given government users with residency requirements nothing published addresses. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified August 23, 2026. No vendor pays for placement.
What quality controls are missing at each?
Each leaves a different scale question open. Hebbia ships grids of thousands of cited answers with no per cell confidence and no published sampling guidance, so quality control at scale is the buyer's to design. Endex ships arithmetic into live valuation models with no measured accuracy at all. Independent reviewers describe Hebbia as expensive with a real implementation behind it; Endex publishes nothing commercially. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified August 23, 2026. No vendor pays for placement.
Where does each publish the most, and the least?
Hebbia publishes most on adoption and on citation down to the sentence. It says nothing on per cell confidence, extraction accuracy or security artifacts. Endex publishes most on its model chain, named to the version, and on cell level attribution inside Excel. It names no customer firm and publishes no accuracy for what it ships, no security artifact and no price. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified August 23, 2026. No vendor pays for placement.
Related comparisons
Other published head to head assessments involving these vendors or their closest peers. The full set for this category is on the Capital Markets & Research AI page.
The control question travels in opposite directions. At Endex, the buyer builds the approval gate the design removed, because nothing is described between the agent's reasoning and its writes into a live valuation model, and no measured accuracy exists for the arithmetic it ships.
At Hebbia, the buyer builds quality control for scale, because a grid of thousands of cited answers ships with no per cell confidence and no published sampling guidance, and no aggregate extraction accuracy exists either. Both run on named external models, disclosed mainly because the providers published case studies as marketing, and neither states what those providers retain from confidential deal material. Neither shows a security artifact an outside buyer can verify.
Hebbia publishes none despite adoption reaching government users whose residency requirements nothing published addresses, and Endex offers adjectives in place of credentials. Commercially, independent reviewers describe Hebbia as expensive with a real implementation behind it, and Endex publishes no price, though a marketplace listing for it exists.