Scale GenAI Without Compromising Confidentiality or Professional Responsibility.
Legal AI operates where privilege, professional ethics, and personal practitioner liability intersect. Mitigate the confidentiality, research integrity, and professional responsibility risk GenAI introduces from pre-deployment through production, in one platform.
Legal AI Risks Don't Stay Inside the Firm.
The risks differ across research, client communications, e-discovery, and agentic workflows. So do the controls required. WonderSuite adapts to each.
Legal Research & Drafting AI
Evaluate AI-generated research, briefs, and contracts for hallucinated citations and misrepresented precedent before they reach a client or a court. Courts are sanctioning attorneys for AI errors their review process failed to catch.
Client-Facing & Advisory AI
Enforce privilege and scope boundaries across every client interaction in real time. An AI that discloses confidential information or creates an unintended attorney-client relationship does so before any human reviews the output.
e-Discovery & Document Review
Test document review AI against privilege leakage and adversarial manipulation before it processes matter-sensitive materials. A single inadvertent disclosure in litigation can be case-dispositive and irreversible.
Agentic Legal Workflows
Monitor AI agents operating across matters, clients, and jurisdictions. Conflicts of interest and privilege contamination compound at every step — and rarely surface until a client or a court notices something wrong.
We've seen the worst.
So your clients don't have to.
Rabbit Hole is the adversarial engine behind WonderSuite. Built on a decade of global trust and safety research and billions of real-world adversarial and manipulative samples, instead of only synthetic data, so that you can deploy legal AI with confidence that your system has been tested against the threats it will actually face not the ones someone imagined in a lab.
One Platform. Every Lifecycle Stage.
Built For Legal Ethics Rules and Frameworks.
AI Governance
The AI-specific competence standard. This replaces both 1.1 and 512 separately and is the entry point for any US law firm conversation about AI governance
ACA
Section 1557 requires equitable access to healthcare programs, including AI-driven care delivery. WonderFence monitors patient-facing AI across 100+ languages, ensuring consistent behavior regardless of how patients communicate. WonderCheck detects performance drift across demographic and linguistic segments as models evolve.
HITECH
HITECH extends HIPAA's enforcement to electronic PHI and ties penalty severity to the strength of your safeguards. WonderFence detects and redacts ePHI at the interaction layer and logs every interaction for an audit trail that demonstrates reasonable controls are in place.
Your Frameworks and Policies
Upload any internal or regulatory policy directly into WonderSuite and enforce it across your full AI lifecycle, giving your institution the flexibility to maintain compliance with virtually any framework or regulation.
Partner with Alice legal AI that's defensible by design
Talk to our legal AI team about your specific exposure across research tools, client-facing systems, and agentic workflows and what you need in place before a client, a court, or a bar association asks.
Privilege Boundary Enforcement
Detect and block AI outputs that disclose confidential matter information, create unintended attorney-client relationships, or breach scope boundaries before they reach a client.
Research Integrity Control
Identify hallucinated citations, misrepresented precedent, and inaccurate legal analysis in AI-generated research and drafts before they reach a practitioner, a client, or a court.
Defensible Governance on Demand
Generate the audit trails and evidentiary documentation your firm needs for bar ethics disclosures, client assurance conversations, and internal risk oversight built into every interaction from day one.
Pre-Deployment Validation
Red team legal AI before launch against adversarial scenarios specific to privilege, confidentiality, and research integrity. Know what fails before any matter data enters the system.
Production Drift Detection
Monitor how legal AI behaviour changes after model updates and prompt changes. Catch regressions before they introduce new privilege risks or produce outputs that wouldn't survive bar scrutiny.
Flexible Deployment
Meet data residency, security, and jurisdiction-specific compliance requirements without slowing AI rollout. Deploy on-premises or in the cloud, whichever your firm or clients require.
Questions Legal Service Provider Teams Ask Us
Our attorneys already review AI outputs before anything goes to a client or a court. Why do we need additional controls?
Review catches many failures. It doesn't catch all of them, not consistently, and not under time pressure. The Mata v. Avianca sanctions happened despite attorney sign-off. What systematic controls add is not a replacement for judgement. It's coverage for the conditions under which judgement fails. The duty of competence under Rule 1.1 requires understanding how your tools fail, not just reviewing outputs after the fact.
How does WonderSuite protect privilege in AI systems that touch multiple matters?
Privilege contamination in AI is structural, not incidental. A model operating across matters can surface information from one client context in another — in ways that don't announce themselves in the output. Existing information barriers weren't designed for this. WonderFence enforces matter-level boundaries at the model layer. WonderBuild tests for cross-matter leakage before any client data enters the system.
Every state bar is writing different AI guidance. How do we keep up?
You can't ,and you shouldn't try to chase every formal opinion as it's issued. The better approach is governance infrastructure that's jurisdiction-aware from the start: controls that apply differently based on practice area, matter context, and where the work is being done. When new guidance arrives, it maps to policy configuration. Your infrastructure doesn't change. Your audit trail already supports whatever disclosure that jurisdiction requires.
A client just asked us to demonstrate how we govern AI use in our practice. What do we show them?
A structured record, pre-deployment test results, production monitoring logs, privilege boundary configurations, and policy alignment evidence. The firms that answer this question well aren't scrambling to produce documentation. They built governance into their AI systems from day one. That's a competitive position, not just a compliance obligation.
Implement Real-Time AI Governance.
See how WonderBuild, WonderFence, and WonderCheck work together to protect privilege, eliminate hallucination risk, and keep legal AI defensible across its full lifecycle.
See WonderSuite in Action