More leverage per attorney hour on the cases that matter.
WOLF AI is built for qui tam and FCA teams pursuing large-scale fraud against the government. Less time buried in records, more time building the case, and more leverage to help recover public money.
Book a DemoBuilt differently because the stakes are different.
Qui tam cases help recover stolen public money. That deserves infrastructure built for it, not generic AI summaries.
Reduce the evidence bottleneck
Evidence organization can consume substantial attorney time. WOLF AI is designed to turn that work into structured, source-linked output, but no verified time-savings claim is published yet.
Source-linked, not black-box
Every output traces back to a specific document, page, and passage. Attorneys verify; they do not guess, especially when taxpayer money is on the line.
Built around qui tam workflows
Not a generic legal AI tool. WOLF AI is designed around how plaintiff-side FCA and whistleblower teams actually build fraud cases.
Built for sensitive case work
Designed around careful data handling, encrypted storage, access controls, and auditable workflows so firms can evaluate WOLF AI against their own requirements.
The tools FCA teams use today, and where they fall short.
Generic AI was not built for qui tam. eDiscovery was built for defense. Manual review does not scale. WOLF AI is built for the plaintiff-side fraud case.
| Capability | Generic AI (ChatGPT, Claude) | eDiscovery (Relativity, etc.) | Manual review (associates + excel) | WOLF AI |
|---|---|---|---|---|
| Source-linked outputs (document + page + passage) | · | Partial | ||
| Purpose-built for FCA / qui tam theories | · | · | ||
| Source-linked chronology workflow | Partial | · | · | |
| Claim-by-claim evidence mapping | · | · | Partial | |
| Damages workup support | · | · | Partial | |
| Complaint-ready output packets | · | · | Partial | |
| Scales across hundreds of documents | Partial | · | ||
| Attorney reviewable and editable | Partial |
Based on typical deployments. Every firm's stack differs, so we are happy to walk through specifics on a call.
One platform from intake to filing
WOLF AI covers the full FCA case preparation lifecycle, so teams stop switching between tools or losing critical context.
Source-linked chronology
Provider submits claim CPT 99215 for patient PT-0241
billing_export.pdf · p. 14Medical record shows 8-minute encounter, not 40+
emr_records.pdf · p. 92Internal compliance email flags upcoding pattern
email_thread_048.pdf · p. 3Pattern continues; 41 further claims at same code
billing_export.pdf · pp. 14-31+ 312 further events across the matter
Workflow hypotheses we are testing
Our working assumptions about plaintiff-side FCA workflows. We are recruiting practitioners to correct them.
“The biggest bottleneck is organizing evidence across hundreds of documents before the theory of the case can be built. Cutting that time changes the economics of a contingency practice.”
Hypothesis: evidence organization
“Attorneys need outputs they can verify. Source-linked chronologies with page-level citations are table stakes for anything used on a filing.”
Hypothesis: verifiable outputs
“Generic AI summarizes. Qui tam cases need something that traces: claim to document, document to regulation, regulation to damages.”
Hypothesis: tracing over summarizing
Which standards is this built against?
Traceability and human review are not house style. They are what the published frameworks and the statute already ask of you.
The NIST AI Risk Management Framework organizes trustworthy AI around functions it calls Govern, Map, Measure, and Manage, and treats traceability and human oversight as design requirements rather than optional additions. Source-linked output is the practical form that traceability takes in a litigation workflow.
Comment 8 to ABA Model Rule 1.1 states that maintaining competence requires a lawyer to keep abreast of "the benefits and risks associated with relevant technology." Adopting an AI-assisted workflow and verifying what it produces are treated as two halves of the same professional obligation, not as separate choices.
Source: ABA Model Rule 1.1: Competence (including technology)
A qui tam complaint is filed in camera and, under 31 U.S.C. § 3730(b)(2), "shall remain under seal for at least 60 days" and is not served on the defendant until the court so orders. Courts routinely extend that period, so the confidentiality obligation on the record set is measured in months or years, not weeks.
More than a platform, a partner
Built to be corrected by practitioners
WOLF AI is an early-stage prototype. We are recruiting qui tam practitioners to correct our workflow assumptions before expanding the product.
Fits into current workflows
Designed to sit alongside your existing document storage and review process during early deployments.
Hands-on onboarding
Our team works directly with your firm on setup, feedback loops, and early adoption.
See WOLF AI in action
Book a focused demo to see how WOLF AI structures FCA case preparation for your team.
Book a Demo