Ship compliant AI agents in days, not months.
ZebraTruth is the runtime authorization layer that determines, before they happen, whether AI agents’ real-world actions are legal and compliant — against laws, regulations, industry practices, and companies’ internal policies. For any action, any regulated industry, across any geography.
Built for regulated brands — pharma, healthcare, financial services, and food & beverage.
Illustrative compliance check
credit-agent / adverse-action notice
Adverse-action reason needs review
Consumer credit · Hold
Required notice details need confirmation
Customer communication · Review
Human sign-off required before sending
Firm approval policy · Hold
Action and check captured for review
Audit record · Recorded
Trusted by teams in media, publishing, financial services, and sports
Compliance at the point of action.
A bank's AI agents act across different business lines. Each proposed action needs the right rules and internal policies applied before it reaches a customer, a market, or a regulator.
Client & financial crime
An onboarding agent prepares a KYC journey
Identity checks, customer due diligence, and bank policy
Credit & customer operations
A lending agent prepares an adverse-action notice
Required reasons, disclosures, and customer treatment
Markets & trading
A markets agent prepares an order-routing disclosure
Execution obligations, relevant rules, and internal controls
Financial promotions are one use case. Customer journeys, advice, credit, and trading bring many more.
Faster compliance, with less manual work.
Runtime checks shorten the wait for a compliance decision and leave more capacity for the cases that need a person.
Compliance turnaround
4 days
Down from 9 weeks
Compliance-team workload
1/3
Reduction in workload
Figures supplied by ZebraTruth. Results depend on the workflow.
Compliance that moves at the speed of AI.
ZebraTruth's compliance agent works with your AI agents inside the workflow. It checks a proposed real-world action before execution, using the rules and institutional context that apply to that action.
Keep human oversight for judgment calls. Give compliance teams a defensible record of what was checked and why.
Agent-to-agent compliance
Before the action, not after the incident.
Proposed action
A bank AI agent requests permission to act.
Contextual check
ZebraTruth applies relevant laws, regulations, industry practices, and the bank's policies.
Decision & evidence
The workflow receives a decision, explanation, and audit record before any action can proceed.
100+
Use cases across the bank.
From a KYC journey to a suitability report, a credit notice, or a trading disclosure. Financial promotions are only one part of the picture.
Client & financial crime
Onboarding and KYC, customer due diligence, fraud warnings, AML and sanctions
Advice & portfolio
Suitability reports, risk profiles, portfolio descriptions, and robo-advice journeys
Product & disclosure
Financial promotions, product documentation, client communications, and regulatory filings
Firm & governance
AI policies, model-risk standards, validation summaries, and board reporting
Credit & customer operations
Pre-contract information, adverse-action notices, servicing, and collections
Markets & trading
Best-execution disclosures, research, investment recommendations, and conduct review
Check the action before the agent acts.
From a KYC journey to a consumer-credit notice or trading disclosure, the compliance check happens in the agent workflow. This gives your teams a chance to resolve an issue before an action reaches a customer or a market.
Connect your agents
Bring ZebraTruth into the workflow where an AI agent prepares an action. The compliance check becomes part of the process, not a separate review at the end.
Check in context
Before the action proceeds, check it against applicable laws, regulations, bank policies, and the facts of the case. Route issues that need judgment to a person.
Return a traceable decision
Send the outcome back into the agent workflow with an explanation and audit record. Teams can review the action, the rules used, and the reason for the result.
The rules behind every check.
A proposed action only makes sense in context. ZebraTruth brings together external requirements and your institution's own guidance so each agent check can be evaluated against the right sources.
Laws & regulations
The legal requirements that apply to a particular action and jurisdiction.
Regulatory guidance
Supervisory expectations, published guidance, and interpretations.
Enforcement cases
Past actions that show how rules have been applied in practice.
Industry practices
Sector-specific standards for financial services and other regulated work.
Company policies
Your institution's controls, approval requirements, and risk appetite.
Internal guidance
Institutional knowledge that is not available in a general-purpose model.
The applicable rules depend on the action, business line, institution, and jurisdiction.
Built for agentic compliance in the most regulated industries.
The same question runs through every regulated workflow. Can this agent take this action, here and now, under the rules that apply?
Financial services
Check proposed actions across client onboarding, advice, credit, customer communications, and markets against relevant obligations and bank policy.
Pharma
Apply regulatory and internal requirements to AI-supported workflows, with the right review before a consequential action.
Healthcare
Give AI agents context for patient-facing communications, claims, and privacy-sensitive work.
Food & beverage
Bring product, labeling, and promotional requirements into the workflows where AI agents prepare an action.
Give compliance teams oversight at agent speed.
ZebraTruth does not replace your reviewers. It gives compliance officers and counsel visibility into agent actions, with a way to review the exceptions that need a human decision.
Know what was checked
See the proposed agent action, the applicable requirements, and the reason a check passed, paused, or needs a reviewer.
A recommendation, not legal advice
ZebraTruth identifies issues and recommends a next step. It does not give legal advice. Your team decides how to resolve the case.
Escalate what needs judgment
Give reviewers the context for exceptions while routine checks stay inside the agent workflow.
Keep a defensible record
Maintain an audit trail of the proposed action, the rules checked, the result, and any human review.
Why not just ask an LLM? Because LLMs were not built for compliance.
ZebraTruth brings laws, regulatory guidance, enforcement practice, and your own policies into checks that run where your AI agents act.
Compliance is unwritten knowledge
Interpretations, enforcement cases, and internal policy do not all live on the open web. A general model may miss the context behind a bank's decision.
Defensible, not just an answer
A chat response alone does not show which action was checked or which rules applied. ZebraTruth connects the decision to its supporting evidence and audit record.
Built for changing requirements
Laws, regulatory expectations, enforcement practice, and institution-specific policies evolve. Compliance knowledge must be maintained as those requirements change.
Built by operators from regulated markets.
Compliance, AI policy, and go-to-market leaders who have built and scaled in the most regulated industries in the world.
Fahd Rachidy
Founder & CEO
Repeat founder with two AI exits in regulated markets. Co-founded Scientific Beta, from 0 to acquisition by SGX for $200M+. Clients included Morgan Stanley, BlackRock, CalPERS, Fidelity, Amundi, and HSBC.
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Al Lavassani
AI Policy
Chief Privacy Officer (UC Office), VP AI Governance & GRC. Previously Meta, SoFi, VISA, and Wells Fargo.
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Jennifer Lada
AI Compliance & Legal Corpus
Partner at Holland & Knight LLP. Regulatory and compliance corpus, plus AI-agent supervisory frameworks.
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Diane Weiss
Strategy
25+ years driving product innovation and strategic transformations at Intuit, Apple, HP, Oracle, and Sun Microsystems.
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Thomas Neubert
Sales
Previously VP/GM Sales at Intel Corporation and Deutsche Telekom.
Connect on LinkedInSee your AI agent's actions checked in a 45-minute working session.
Bring a real use case from your workflow. We will walk through the proposed action, the compliance context, and where your team would review the result.