Hadrius vs Shiboleth (2026)
Both keep a person on every decision, one regulatory perimeter apart. Hadrius runs the compliance program of the registered adviser and broker dealer. It captures communications across more than thirty channels, reviews marketing against the advertising rules, monitors personal trading and automates attestations. The compliance officer adjudicates every flag, because the founders operated a registered adviser and know the supervisory obligation attaches to a person. More than 500 firms are live, with a zero data retention commitment at the model layer. Shiboleth runs the compliance program of the consumer lender and the sponsor bank. It audits conversations, manages complaints, reviews marketing and drafts regulatory reports as first versions a team finishes, with true source materials behind every finding as the stated design principle. Its single named customer is a bank widely regarded as the leading banking as a service sponsor institution. The designs agree about where the human sits and share the same silence about what the machine misses: neither publishes recall or detection anywhere, the number this category's failure mode turns on. What differs is who bears the unmeasured errors. At Hadrius it is the adviser whose informal register draws uneven classifier scrutiny into a supervisory record. At Shiboleth it is the flagged fintech partner and the audited borrower. Neither describes a route for them.
- Your firm is a registered adviser or broker dealer. Communications across thirty plus channels, marketing review, trading surveillance, attestations and audit ready examination evidence run in one platform built by founders who operated one.
- Your scale wants proof at your size. More than 500 firms are live, with a chief compliance officer quoted by name and implementation reported in days.
- Your model layer should retain nothing. The stated zero data retention commitment keeps firm communications out of downstream storage, a concrete answer this category rarely gives.
- Your market is consumer lending or sponsor banking. Conversation audits, complaint management, marketing review and drafted regulatory reports serve lenders, with a monitoring layer for banks overseeing fintech programs.
- Your reference bar is the leading institution. A bank widely regarded as the leading banking as a service sponsor is the named customer, with the principal industry association's head quoted on the company.
- Your findings must carry their evidence. True source materials sit behind every finding, oversight is human at every step, and reports arrive as drafts your team finishes rather than starts.
This comparison is published by AI FinTech Index, an independent research platform that publishes independent ratings of AI vendors for financial services. Hadrius and Shiboleth 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
| Hadrius | Shiboleth | |
|---|---|---|
| Primary category | Compliance, Surveillance & RegTech | Compliance, Surveillance & RegTech |
| Founded | Not published | 2023 |
| Headquarters | New York, New York, United States | San Francisco, California, United States |
| Website | www.hadrius.com | www.shiboleth.ai |
Side by Side
Select any grade to read the note behind it.
| Axis | H Hadrius |
S Shiboleth |
|---|---|---|
| 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
Hadrius
Hadrius runs the compliance program of the registered adviser and broker dealer. It captures communications across more than thirty channels, reviews marketing against the advertising rules, monitors personal trading and automates attestations. The compliance officer adjudicates every flag, because the founders operated a registered adviser and know the supervisory obligation attaches to a person. It is live at more than 500 firms, with a zero data retention commitment at the model layer. According to the AI FinTech Index, no recall or detection rate is published anywhere, the number the category's failure mode turns on, and the published false positive reduction trades against exactly that detection. The scored subject is the firm's own adviser, whose informal register draws uneven classifier scrutiny into a supervisory record with no described contest route. The retention commitment stops short of naming whose infrastructure content traverses.
Source: AI FinTech Index, 2026
Shiboleth
Shiboleth runs the compliance program of the consumer lender and the sponsor bank. It audits conversations, manages complaints, reviews marketing and drafts regulatory reports as first versions a team finishes. True source materials behind every finding is the stated design principle. Its single named customer is a bank widely regarded as the leading banking as a service sponsor institution. According to the AI FinTech Index, its position between parties is the structural question. The platform observes failures on both sides of the sponsor and fintech relationships it monitors and serves competitors in the same programs, yet it publishes no separation terms. A model flagged finding can reach program termination for the fintech, and the audited borrower has no stated notice. No detection rate is published anywhere, and the retained tenth behind the 90 percent automation claim is undefined.
Source: AI FinTech Index, 2026
Common questions
How do Hadrius and Shiboleth relate?
Adjacent perimeters, same design. Hadrius runs securities compliance for registered advisers and broker dealers, Shiboleth runs consumer lending compliance and sponsor bank fintech monitoring, and both mandate human adjudication with the machine as reviewer of volume. 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?
Differently shaped and both real. Hadrius shows breadth, more than 500 firms with an attributable testimonial. Shiboleth shows precision, one named customer widely regarded as the leading sponsor institution in its market. 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 number does neither publish?
Recall. Neither states what its system misses, which is the supervisory failure mode both exist to prevent, and Hadrius's false positive reduction actively trades against it. 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.
Who is affected without recourse at each?
Hadrius's adviser flagged by classifiers with uneven error across dialect and register, and Shiboleth's monitored fintech partner and audited borrower, none of whom has a described contest or notice route. 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 Compliance, Surveillance & RegTech page.
Both keep a person on every decision, and the unmeasured number is the one their designs exist to manage. Neither publishes recall, detection rate or any account of the violation missed, which is invisible by definition until an examiner finds it. Hadrius pairs the gap with a published false positive reduction that trades against exactly that detection. Shiboleth pairs it with a 90 percent automation claim whose retained tenth is undefined.
The affected parties differ with the perimeters and share the absence of a route. At Hadrius the scored subject is the firm's own adviser, and language classifiers carry uneven error across dialect, first language and register into a supervisory record with no described contest.
At Shiboleth the parties are the fintech partner whose program a model flags to its sponsor bank, with consequences reaching termination, and the borrower whose recorded conversation was audited without any stated notice. The platform sits between both sides of the relationships it monitors and serves competitors in the same programs, with no published separation terms. Neither publishes an attestation, hosting arrangement or retention schedule for archives held under preservation rules. Hadrius alone makes a model layer commitment, zero retention, without naming the providers.