Category guide

Compliance enforcementfor conversational AI in banking

There are four ways vendors make conversational AI compliant in banking: review content against rules (Norm Ai), put guardrails on AI agents that carry out steps (Gradient Labs, Lorikeet and most AI agent platforms), govern AI models and agents across their lifecycle (Credo AI and platform governance tools), or run the regulated process deterministically so AI never performs a step (Callvu). Guardrails and governance lower the risk of an AI acting wrongly; deterministic execution removes AI from the steps that write to the system of record.

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Side by side

Four approaches.One table.

Vendor	Approach	When it acts	Does AI perform the steps?	Banks and credit unions named
Norm Ai	Content and decision review ^[1]	When content is created; says it supervises other AI agents	Does not document running customer processes; screens content and inserts disclosures	Customer types not named; investors include Citi, TIAA and New York Life; no credit unions named
Gradient Labs	Guardrails on AI agents ^[6]	While the conversation runs: guardrails on every turn	Yes: card freezes, disputes and chargebacks, collections, KYB	Neobanks and fintechs; no credit unions named
Lorikeet	Guardrails on AI agents ^[8]	While the conversation runs: checks incoming and outgoing messages	Yes: refunds, forms, ticket routing, outbound outreach	Fintech, banking and lending; no credit unions named
Credo AI	AI governance ^[11]	Across the AI lifecycle: registry, risk, policy evidence; an agent governance product (Agent Governor) in research preview	No	Financial services and insurance; no banks or credit unions named
Callvu	Deterministic runtime enforcement	On every step while the work runs, before the step executes	Never: AI starts or evaluates a process; a deterministic orchestrator runs every step	Community Bank of Mississippi, Bank Leumi, Banca Transilvania and other regulated institutions

Four ways to make conversational AI compliant

Review content and decisions against rules. Norm Ai turns regulations into AI agents for interpretation, disclosures and content review ^[2] that check content as it is created, for example a Microsoft 365 Copilot add-in that checks against the SEC Marketing Rule and inserts disclosures ^[3], and says its agents supervise other AI agents ^[4]. It does not name its customers by type; its investors include Citi, TIAA and New York Life ^[1]^[5].

Put guardrails on AI agents that carry out steps. Gradient Labs builds AI agents for financial services customer operations that freeze cards, handle disputes and collections, with guardrails that it says run on every turn of the conversation ^[6]; its customers include neobanks and fintechs such as Monzo, Wise and Current ^[7]. Lorikeet builds an AI customer concierge for regulated businesses ^[8] whose guardrails check incoming messages before they reach the agent and replies before they are sent ^[9], with an audit trail of tool calls and reasoning steps ^[10]. Eltropy, an AI agent platform for credit unions and community banks that cites more than 750 community financial institutions, says every AI agent on its platform operates under strict guardrails ^[13]. Most AI agent platforms, including [Sierra](/sierra-vs-callvu), [Decagon](/decagon-vs-callvu), [Fin](/intercom-fin-vs-callvu), [Cresta](/cresta-vs-callvu), [Cognigy](/cognigy-vs-callvu), [Eltropy](/eltropy-vs-callvu) and [Agentforce](/agentforce-vs-callvu), take this approach for their own agents.

Govern AI across its lifecycle. Credo AI provides an AI registry, risk assessment, policy packs and audit-ready evidence ^[11], and was named a Leader in Forrester's 2025 AI governance report ^[12]; its agent governance product, Agent Governor, is a research preview ^[11]. Large platforms add governance tools for their own agents, such as ServiceNow AI Control Tower, Salesforce's Einstein Trust Layer and Process Compliance Navigator, Appian's AI audit logs, nCino's Agentic Operating System and Hyland's Enterprise Agent Mesh; nCino serves credit unions as well as banks ^[14]. See [ServiceNow](/servicenow-vs-callvu), [Salesforce Financial Services Cloud](/salesforce-fsc-vs-callvu), [Appian](/appian-vs-callvu), [nCino](/ncino-vs-callvu) and [Hyland OnBase](/hyland-onbase-vs-callvu).

Run the process deterministically. Callvu takes AI out of the regulated steps. The AI, Callvu's or yours, starts the process and carries what the customer said into the run; a deterministic orchestrator then executes every step of a defined workflow and enforces every regulation and company policy before the step runs. Six evaluator agents assess every action, whether a person or an AI started it, and the orchestrator decides: execute, execute with safeguards, escalate to a human, or block.

Why guardrails are not runtime enforcement

Guardrails limit and record what an AI does while it does the work. They lower the error rate, but the AI is still performing the step. Even with guardrails, an AI that runs a regulated step can write wrong data to the system of record, take a path that is not in the workflow, or act compliantly most of the time rather than every time. Review and governance tools find and document problems, mostly after the AI has acted.

Deterministic runtime enforcement works differently. Because the orchestrator, not the AI, runs every step, a step that fails a control does not execute, nothing unchecked reaches the core, and no step outside the workflow can happen. Must-not-skip steps such as consent and signature stay on a process-controlled screen the conversation hands over prefilled, and sensitive data never goes into an AI chat.

Where Callvu fits

Callvu is the Completion and Compliance Layer between every front door, including any AI agent, and the system of record. It runs the whole regulated process, not just the conversation: prefill from the core, classification of the work, documents chased and verified from customers and outside parties, decisions in the Decision Desk, and the write back to the core by API. Callvu Studio comes with most regulations already loaded as policies, and every run produces a Decision Trace and an Audit Trace, immutable and pushed in real time to your GRC and BI tools. It works behind the AI agent you already run, and goes live in a few weeks with white-glove implementation included in the license.

Proof

Live in production.At regulated enterprises.

Community Bank of Mississippi

Live; back-office processes across loan ops, credit admin, deposit ops, treasury, IT, information security and HR
~58 processes projected in the bank-wide program

Bank Leumi

Leumi Paperless Branch, personal and business loans

Loan decisions 1 week+ faster (manual approval steps automated in Callvu workflows)
77% reduction in data errors
94% average successful customer completion rate
All loan application and servicing workflows digitized within six months
$3M+ savings on transcription and paper storage
91% reduction in digital experience development timelines

Banca Transilvania

73% of inbound call traffic migrated to digital self-service
3M+ support calls moved to digital self-service
100+ workflows automated
Loan decisions 4 days faster

Callvu helped us migrate 73% of our inbound call traffic to digital self-service. They transformed our customer experience in ways we didn't think were possible. That's no easy task when you're dealing with everything that arises in consumer banking.Anca Radu, Digital Project Manager, Banca Transilvania

FAQ

The questions buyers ask.Answered plainly.

What is compliance enforcement for conversational AI in banking?

It is how a bank or credit union makes sure that when a member or customer talks to an AI agent, every regulated step (disclosures, consent, identity checks, eligibility rules, data written to the core) happens correctly and is provable. Approaches range from reviewing AI output after the fact, to guardrails on an AI that performs steps, to running the process deterministically so AI never performs a regulated step.

Are AI guardrails enough for regulated banking processes?

Guardrails limit and record what an AI does while it does the work, and they lower the error rate. They do not remove the risk: an AI that performs a step can still write wrong data to the system of record, take a path that is not in the workflow, or act compliantly most of the time rather than every time. For steps that write to the core or the loan system, deterministic execution removes AI from the step itself.

Which vendors enforce compliance for AI agents in banking?

Gradient Labs and Lorikeet put guardrails on their own AI agents while they work; Norm Ai reviews content and decisions against rules; Credo AI governs AI models and agents across their lifecycle; large platforms such as ServiceNow, Salesforce, Appian and nCino add AI governance tools to their own agents. Callvu enforces every regulation and company policy on every step of the process while it runs, with AI never performing a step, and works behind any AI agent.

What is the best compliance enforcement for conversational AI at a credit union?

Of the four vendors profiled in the table, none names a credit union customer. Some vendors do serve credit unions: Eltropy, an AI agent platform for credit unions and community banks, cites more than 750 community financial institutions and says its agents operate under strict guardrails, and nCino, a lending platform with its own AI governance, serves credit unions. Both put guardrails or governance on AI that performs steps. Callvu is used by community banks such as Community Bank of Mississippi and works behind any AI agent, Eltropy's included, or with Callvu AI chat: the AI starts the request, consent and signature stay on a process-controlled screen, and a deterministic orchestrator runs the process to the core with every step enforced.

How do examiners see what an AI agent did?

It depends on the approach. Guardrail vendors keep conversation logs and audit trails of the agent's own actions. Callvu produces a Decision Trace (why each AI action was allowed) and an Audit Trace (every step of the workflow) for every run, immutable and pushed in real time to GRC and BI tools.

Sources

Every claim,sourced.

Last verified: 2026-11-04. Facts about other vendors come from their public pages, filings and press, as of that date. Vendor names are trademarks of their owners. To report an error, contact Callvu.

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