Hebbia vs Rogo (2026)
The grid against the agent. Hebbia is built to analyse and stop there: agents decompose a question, read whole documents rather than retrieved fragments, and fill a matrix where every cell carries a citation resolving to the exact sentence that produced it, the strongest anti fabrication design in this index, with every cell individually overwritable. Its adoption is the widest in the research lane, more than 40 percent of the largest asset managers and a published 250 billion tokens processed monthly. Rogo is built to finish: the same class of analysis, then committed into spreadsheets, presentations and the data room, with personalised teasers generated and outreach sequences run and tracked, closing the workflow without a banker re keying anything. That difference is the decision. A firm whose supervision model requires human review before anything leaves gets a natural fit from the grid; a firm buying throughput gets it from the agent, and inherits the obligation to build the approval gates Rogo does not describe. Both disclose their model chains unusually well, and both leave retention of confidential deal content by those providers unstated.
- Verification is the workflow. Every cell resolves to the exact page, paragraph and sentence behind it, the strongest anti fabrication design in this index, and every cell can be flagged or overwritten, so review happens inside the artifact.
- Adoption breadth is the proof. More than 40 percent of the largest asset managers, 250 billion tokens processed monthly, and independent reports of thirty to forty hours saved per deal and credit agreement review cut by three quarters.
- Analysis without action is the safer posture for your supervision model. The platform reads fixed document sets and produces a reviewable grid; it does not act in other systems, so nothing reaches a counterparty or a deal file unreviewed.
- You want the work finished, not surfaced. Rogo commits completed output into spreadsheets, presentations and the data room, and runs tracked outreach to buyers, closing workflows Hebbia hands back to a person.
- Deal team system integration decides it. Reading from market databases, filings, CRM and the data room and writing back into the firm's own tools is the harder half of the problem, and it is Rogo's design centre.
- Sell side depth is your segment. Named adoption across bulge bracket and elite advisory firms with an investment bank's growth arm in the round fits an advisory house more precisely than a cross industry analysis platform.
This comparison is published by AI FinTech Index, an independent research platform that publishes independent ratings of AI vendors for financial services. Hebbia and Rogo 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
| Hebbia | Rogo | |
|---|---|---|
| Primary category | Capital Markets & Research AI | Capital Markets & Research AI |
| Founded | Not published | Not published |
| Headquarters | Not published | New York, New York, United States |
| Website | www.hebbia.com | rogo.ai |
Side by Side
| Axis | H Hebbia |
R Rogo |
|---|---|---|
| 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 |
The short version of each
Hebbia
Hebbia analyses and deliberately stops there, agents decomposing a question, reading whole documents rather than retrieved fragments, and filling a matrix where every cell carries a citation resolving to the exact sentence that produced it, every cell individually overwritable, which the AI FinTech Index records as the strongest anti fabrication design it holds, with the widest adoption in the research lane, more than 40 percent of the largest asset managers and 250 billion tokens monthly. The index notes its providers' retention of confidential deal content is unstated, engagement separation between opposing institutions is undescribed, and no aggregate accuracy is published.
Source: AI FinTech Index, 2026
Rogo
Rogo finishes the workflow, committing analysis into spreadsheets, presentations and the data room, generating personalised teasers and running tracked outreach sequences so nothing is re keyed by a banker, named at the top of advisory. The AI FinTech Index records the closed workflow as both the capability and the supervision question: no approval gate is described before work commits or outreach sends in live transactions, so a firm buying throughput inherits the job of building the gates, with provider retention of confidential content unstated and engagement separation between institutions on opposite sides of the same deals undescribed.
Source: AI FinTech Index, 2026
Common questions
Is Hebbia better than Rogo for deal work?
The grid against the agent. Hebbia analyses and stops there, filling a matrix where every cell's citation resolves to the exact sentence, with every cell individually overwritable. Rogo finishes, committing the same class of analysis into spreadsheets, presentations and the data room, generating teasers and running outreach sequences without a banker re keying anything. A firm whose supervision model requires human review before anything leaves gets a natural fit from the grid; a firm buying throughput gets it from the agent and inherits the job of building the approval gates. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified August 12, 2026. No vendor pays for placement.
What is Hebbia's citation architecture?
The strongest anti fabrication design in this index: agents read whole documents rather than retrieved fragments and every cell in the matrix carries a citation resolving to the exact sentence that produced it, so a reviewer can check any claim against its source before relying on it. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified August 12, 2026. No vendor pays for placement.
How does adoption compare?
Hebbia's is the widest in the research lane, more than 40 percent of the largest asset managers and a published 250 billion tokens processed monthly. Rogo's is the top of advisory named, and its distinctive capability is closing the workflow, which is also its distinctive supervision question. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified August 12, 2026. No vendor pays for placement.
How well do the two disclose their model chains?
Unusually well, mainly because their providers published case studies as marketing, and both leave the same thing unstated: what those providers retain from confidential deal content. Both also serve institutions on opposite sides of the same transactions with no described engagement separation. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified August 12, 2026. No vendor pays for placement.
What deserves specific supervision attention?
Rogo's unreviewed outreach capability, sequences run and tracked against prospective buyers in live transactions with no approval gate described, deserves specific supervision attention. Neither vendor publishes aggregate accuracy or error rates. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified August 12, 2026. No vendor pays for placement.
How does the AI FinTech Index grade Hebbia and Rogo?
Both are graded on the same fifteen capability axes from public sources, each grade traceable to its artifact. The AI FinTech Index records the pair as the grid against the agent, the strongest anti fabrication design it holds against a closed workflow with no described approval gate, with model chains disclosed at both and provider retention unstated at both. The index publishes no composite score and declares no winner.
Related comparisons
Other published head to head assessments involving these vendors or their closest peers. The full set for this category is on the Wealth & Advisory AI page.
Both vendors' model chains are public mainly because their providers published case studies as marketing, and neither states what those providers retain from confidential deal content; both serve institutions on opposite sides of the same transactions with no described engagement separation. Neither publishes aggregate accuracy or error rates, and Rogo's unreviewed outreach capability deserves specific supervision attention.