Multiversal Ventures
Agent Workforce builds and operates full-stack AI agents that perform defined jobs inside regulated industries like healthcare, insurance, lending, and tax. The agents work within a client's existing tools, follow the organization's specific rules, and shadow human workflows before acting autonomously. The company owns the end-to-end solution, including compliance monitoring as regulations evolve, and is revenue-funded as a permanent owner-operator.
- AI Agents
- Artificial Intelligence
- Insurance Technology
- Financial Technology
- Regulatory & Compliance Technology
- Healthcare Technology
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Regulated industries such as healthcare, insurance, lending, and tax rely on skilled staff to perform document-heavy, rules-intensive workflows where errors carry significant cost—rework, audit findings, denials, and fines. These workflows are slow, manual, and difficult to scale, while off-the-shelf AI tools often fail to meet compliance requirements or integrate with existing systems.
Solution
Agent Workforce builds and operates full-stack AI agents that perform defined jobs inside a client's existing tools, following the organization's specific rules and language. Agents shadow human workflows before acting autonomously, and they explicitly state what they will not do. The company owns the end-to-end solution—from research to running system—and keeps agents compliant as regulations change. Multiversal is a permanent owner-operator, revenue-funded, and built to remain operational long-term. The studio model funds initial work, successful solutions become products, and a lab keeps both ahead of evolving regulatory requirements.
Target Audience
Primary customers are organizations in regulated sectors—healthcare, insurance, lending, and tax—where data is sensitive, rules are heavy, and trust is the product. The company targets owners with budget who can decide in weeks, not quarters, and workflows that run on documents and rules where skilled people spend days reading, checking, and re-keying.
Features
- Full-stack AI agents that operate inside a client's existing tools and follow organization-specific rules and terminology
- Shadow-training approach where agents learn by observing human workflows before acting autonomously
- Named products including Fenero (mortgage lending intelligence), Brook (bank-data recovery for Plaid exceptions), Coverage Intelligence (healthcare reimbursement mapping), and GAVEL (payer rulebook API for providers)
- Hammer Labs world models that test software against regulatory rules rather than around them, with three tests: detour survival, definition changes, and data restatements
- Cryptographic proof certificates on every output, with traceability to source document, page, and line
- Replayable audit trails with rules as versioned data and human overrides captured as evidence