Corlytics vs Norm Ai (2026)
One vendor built a human review chain and publishes it; the other argues publicly that human review is the bottleneck to remove. That is the real choice here and it sits deeper than any feature list. Corlytics describes an oversight chain with named roles. A compliance analyst assesses a source, a content specialist sets what gets ingested, and the work returns to a compliance analyst. A quality assurance team checks completeness before anything reaches a client, and a named override path lets a language model summary be replaced by one written manually. Norm Ai leans hard toward autonomy and says so directly. Its platform autonomously produces findings by executing modules against an artifact, and its founder's stated rationale for regulatory agents is that human compliance staff are inevitably too slow to review the outputs. The candor is useful, and nothing public describes a mandatory review step. The products differ accordingly. Corlytics manages regulatory change across more than 120 countries and 2,500 authorities and maps it onto internal policies and controls. Norm Ai encodes regulations and internal policies as executable decision trees that agents traverse against a submitted document, a marketing piece or a communication, and returns a determination, which is closer to a legal opinion than to a monitoring feed.
- Regulatory change is the workload. Coverage spans more than 120 countries and 2,500 authorities with original language text, translations and redlined version comparison, mapped onto internal policies and controls with attestation and traceability, so a firm can evidence to a supervisor how a change was assessed, implemented and communicated.
- Published human oversight is a control your second line requires. The review chain is described with named roles rather than asserted as human in the loop, and the most error prone output, the machine written summary, has a stated manual replacement path.
- You want evidence you can check before you buy. A global bank and a major professional services firm each sold this vendor a product they had built, and named clients include ING, BNY Mellon, Scotiabank, Swiss Re, SCOR and a national securities regulator as a customer.
- Data segregation and governance certification matter. Client data sits in tenanted databases and an ISO 42001 certified AI management system covers the model lifecycle under independent audit, where the alternative publishes no model provider at all.
- The unit of work is an artifact, not a rule change. A compliance or business user submits a document, a marketing piece or a communication and the relevant regulatory agent runs against it and returns findings, which is a different job from monitoring what regulators published this week.
- Traceability to the provision is the transparency you need. Because regulations are encoded through a proprietary representation language into decision trees that agents traverse, a finding traces back to the specific encoded provision that produced it rather than emerging from a score, which very few AI compliance products offer.
- You want someone carrying professional liability. An affiliated law firm sits alongside the software business, led by a former chair of a major firm's executive committee and staffed by former partners from a dozen leading practices, billing on outcomes rather than hours, so a determination delivered through that arm sits inside a liability regime with a regulator and an insurer behind it.
- You want AI to be the product. The act that creates the value, judging a document against an encoded provision, is entirely model work, where the alternative would still have a large saleable content operation without its models.
This comparison is published by AI FinTech Index, an independent research platform that publishes independent ratings of AI vendors for financial services. Corlytics and Norm Ai 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
| Corlytics | Norm Ai | |
|---|---|---|
| Primary category | Compliance, Surveillance & RegTech | Compliance, Surveillance & RegTech |
| Founded | Not published | Not published |
| Headquarters | Dublin, Ireland | New York, New York, United States |
| Website | www.corlytics.com | www.norm.ai |
Side by Side
Select any grade to read the note behind it.
| Axis | C Corlytics |
N Norm Ai |
|---|---|---|
| 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
Corlytics
Corlytics sells regulatory risk intelligence and policy compliance software to financial institutions and to regulators themselves. It classifies regulatory text across more than 120 countries and 2,500 authorities, extracts obligations, entities and dates, and maps change onto internal policies and controls with attestation and traceability. According to the AI FinTech Index, its oversight chain is described with named roles rather than asserted, including a stated manual replacement path for machine written summaries. Its strongest customer evidence is that a global bank and a major professional services firm each sold the company a product they had built. The gaps are no published pricing, no precision or recall for obligation extraction, and no model provider or hosting arrangement named for an engine described only as its own large language model.
Source: AI FinTech Index, 2026
Norm Ai
Norm Ai converts regulations and internal policies into executable form. It encodes them through a proprietary representation language as decision trees that language model agents traverse against a firm's actual artifacts, returning findings on a submitted document, marketing piece or communication. It also operates an affiliated law firm delivering legal work on outcome based pricing. According to the AI FinTech Index, AI is central to the product: removing the models leaves a machine readable rulebook nobody can apply at scale. Part of the group carries professional obligations and malpractice exposure, though nothing published states what the software itself warrants. It leans hard toward autonomy, with the founder arguing human compliance staff are too slow to review outputs. No client is named and no accuracy figure is published. Nothing discloses which models traverse the decision trees or whether submitted artifacts leave the customer environment.
Source: AI FinTech Index, 2026
Common questions
Is Corlytics better than Norm Ai for compliance?
They solve adjacent problems. Corlytics manages regulatory change across more than 120 countries and 2,500 authorities and maps it to internal policies and controls, with a published human review chain and the stronger customer evidence of the two. Norm Ai encodes regulations as executable decision trees and returns a determination on a submitted artifact, with AI at the center of the product and a liability position built on an affiliated law firm. If the workload is regulatory change, it is the first; if it is reviewing documents against rules, it is the second. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified September 5, 2026. No vendor pays for placement.
What is Norm Ai's position on human review?
Explicit and candid. The platform is described as autonomously producing findings by executing modules against an artifact, and the founder's stated rationale for regulatory agents is to enable deployment of other agents in high stakes workflows where human compliance staff are, in his words, inevitably too slow to review the outputs. Nothing public describes a mandatory review step, an escalation path or a confidence threshold forcing referral. Nor is there any account of how a compliance officer contests a determination before it becomes the firm's official finding. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified September 5, 2026. No vendor pays for placement.
How does Norm Ai's law firm affect liability?
Part of the group is a law firm whose partners carry professional obligations and malpractice exposure for the advice they give, and it bills on outcomes rather than hours, which makes it structurally accountable in a way software vendors rarely are. The unresolved part is the boundary: nothing published states what the software itself warrants, how privilege attaches to work passing between the two entities, or where a software determination ends and legal advice begins. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified September 5, 2026. No vendor pays for placement.
How central is AI to each product?
AI is the product at Norm Ai and one layer of a broader business at Corlytics. Strip the models from Norm Ai and what remains is a machine readable rulebook nobody can apply at scale, because the act that creates the value is a model reading a marketing piece or a communication and judging it against an encoded provision. Strip the models from Corlytics and a very large regulatory content operation remains, spanning 120 countries and 2,500 authorities with legal and compliance analysts who can write summaries manually, plus an acquired policy management platform that was standalone until 2023. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified September 5, 2026. No vendor pays for placement.
What questions remain open at each?
At Norm Ai, nothing states which models traverse the decision trees, who supplies them, or whether submitted artifacts leave your environment. Turning a provision into a decision tree is an act of legal interpretation, yet nothing says who reviews the encodings or how a firm challenges a finding it believes wrong. At Corlytics, no precision or recall is published for obligation extraction and classification, and no model provider is named behind an engine described only as its own. Neither publishes a pricing basis, a hosting region or the security attestations their existing institutional clients will already have required. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified September 5, 2026. No vendor pays for placement.
Where does each publish the most, and the least?
Corlytics publishes most on its customer evidence and who it serves, and documents oversight, data segregation and accuracy in part. It says little about pricing or security certifications. At Norm Ai, AI is central to the product and the law firm gives it a partial answer on liability. It says little about oversight and names neither its models nor a client. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified September 5, 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.
The gaps run in opposite directions and both matter. Norm Ai says less than Corlytics about the models beneath it. No public material identifies which language models traverse the encoded decision trees, who supplies them, or whether artifacts submitted for review leave the customer environment to reach them.
The material under review includes client communications, marketing and deal documents at institutions where confidentiality is contractual, and the affiliated law firm adds a second boundary nobody has mapped publicly. Its operational evidence is close to absent despite a client base described as representing more than $30 trillion in assets under management.
Assets under management behind a customer list describes the caliber of the buyer rather than the performance of the software: no client is named, no accuracy figure is published and no case study reports a before and after. Corlytics refers to its engine only as its own large language model, naming no provider, architecture or hosting arrangement.
It publishes no precision, recall or extraction accuracy for obligation extraction, classification or summarization, all testable against a known corpus. Both say little about pricing, hosting and residency, or security attestations. Neither publishes how consistently its system reaches the same determination on the same input.