Scope comparison
WOLF AI vs. Filevine.
Filevine runs the firm: intake, matters, deadlines, documents, and billing, with an AI layer across all of it. WOLF AI runs inside one False Claims Act matter and produces source-linked chronologies and claims maps. A plaintiff-side firm generally needs the first and may separately want the second.
Published · Last reviewed
Written by the WOLF AI product team from each vendor’s own published description, linked on this page and read on 29 August 2026. Vendors update their products continuously, so confirm current capabilities with them directly. WOLF AI is early-stage: PDF-first ingestion, no public production API or MCP server, and no verified public case study. Nothing here is legal advice.
How does Filevine describe itself?
“LOIS is Filevine’s legal AI software for law firms and legal teams that works across every matter: reading, writing, and executing real casework.”
A firm-wide case management platform with a legal AI layer across every matter.
WOLF AI is not an alternative to an eDiscovery platform or a firm-wide case management system. It is a narrower layer that structures the facts of one False Claims Act matter into source-linked chronologies, claims maps, and damages inputs. Most firms evaluating it already run one of the platforms below and should keep it.
When is Filevine the better choice?
- You need a system of record for the practice — intake, matters, calendaring, documents, billing. WOLF AI is none of those and does not intend to be.
- You want one vendor across the whole firm rather than a case management system plus a practice-specific layer.
- Your evaluation is happening now and you need a product in general availability with published references.
- Your FCA matters are a minority of the caseload, in which case the general platform is very likely enough on its own.
When is WOLF AI worth a look?
- Your FCA and qui tam matters are the practice, not a sideline, and the evidence-structuring work in them is the thing that does not scale.
- You need each chronology entry and each mapped allegation to name the document, page, and passage behind it.
- You want gaps made explicit — allegations with no attached passage, claim lines with no supporting note — rather than smoothed over.
How do the two compare, dimension by dimension?
| Dimension | WOLF AI | Filevine |
|---|---|---|
| Category | FCA case-intelligence layer for one matter at a time | Firm-wide case management with a legal AI layer, per its own description |
| Scope of record | The evidence and the work product built from it | The whole matter lifecycle, including intake, deadlines, and billing |
| Practice scope | Plaintiff-side FCA and qui tam only | Across every matter a firm runs |
| Maturity | Early-stage, design-partner program | Established product with a broad plaintiff-side customer base |
| Primary output | Chronologies, claims maps, damages populations — each entry linked to its page | Managed matters and the documents and drafting produced within them |
| Overlap | Real overlap on document handling and drafting support | Real overlap on document handling and drafting support |
| Integration | No public production API or MCP server today | Established integration surface |
What do the numbers say?
The Department of Justice reports that whistleblowers filed 1,297 qui tam lawsuits in fiscal year 2025, the highest number in a single year and a sharp rise on the previous record of 980 set in 2024. Those filings drove more than $5.3 billion in reported settlements and judgments.
Source: DOJ: False Claims Act settlements and judgments exceed $6.8B in fiscal year 2025
Under 31 U.S.C. § 3730(d), a relator receives at least 15 percent but not more than 25 percent of the proceeds when the government intervenes, and not less than 25 percent and not more than 30 percent when it declines and the relator proceeds alone. The Department of Justice describes the typical range as 15 to 30 percent.
Federal Rule of Civil Procedure 9(b) requires that a party "must state with particularity the circumstances constituting fraud or mistake." In practice that is what turns an FCA matter into a document-organization problem: the allegation has to name specific claims, dates, and actors, each traceable to a record.
Source: Federal Rule of Civil Procedure 9(b): pleading fraud with particularity
Common questions
Is WOLF AI a case management system?
No. It does not handle intake for the firm, calendaring, deadlines, or billing. Filevine describes itself as working across every matter; WOLF AI works inside one matter, on the evidence and the work product drawn from it.
Would a firm run both?
That is the expected arrangement for a firm whose FCA practice is substantial. The case management system stays the system of record and the FCA-specific structuring happens alongside it.
Does WOLF AI do intake?
It has a matter intake module for organizing the documents and frame of a single matter, which is a different thing from client intake for the firm. Do not read the shared word as a shared feature.