Automated Financial Contract Risk Extraction in Manufacturing

Revenue Institute's system pairs an AI layer that reads and extracts contract terms with Manufacturing-specific classification logic that maps those terms to your supply chain, customer programs, production calendars, and regulatory obligations - surfacing payment terms, price escalation clauses, customer-owned tooling liability, and compliance riders in context of your actual BOMs and work orders. Unlike generic contract tools, the system understands that a raw materials supplier's 45-day payment term has different cash-flow weight than a maintenance services contract with identical terms, and that a tooling-liability clause means something different on Customer A's program than Customer B's - then flags supply chain and customer concentration risk by cross-referencing contracts against your production dependency on each supplier and program. The result: Finance sees actionable risk signals tied to plant-floor reality, not raw data.

Yes. For ITAR-controlled supplier agreements, the system operates in air-gapped mode if required. Extraction happens server-side; Finance teams control all data access via role-based permissions tied to your SAP or Oracle user hierarchy. Audit logs track every extraction, review, and approval for regulatory compliance.

We work the C.O.R.E. Method, with a working system live inside the first 100 days. Weeks 1-3 audit the work: system architecture design and integration with your SAP S/4HANA, Oracle, or Epicor environment. Weeks 4-10 build: model training on your historical contracts and supplier data, Finance & Accounting team training, and pilot testing with 20-30 live supplier contracts. Weeks 11-14 deploy: full production rollout and handoff. A rollout like this is scoped to show measurable results (reduced review cycle time, first contract risks surfaced) within 60 days of go-live, with full ROI visibility by month 6.

Generic tools read the document; this system reads the document against your operation. A standard contract reader treats every clause equally - it cannot tell that a 45-day payment term on a raw materials supplier feeding a critical BOM line threatens cash flow in a way the same term on a maintenance agreement never will, or that a tooling-liability clause carries different exposure depending on which OEM customer's program it's tied to. Because the classification layer cross-references contracts against your active BOMs, work orders, and production calendars, the flags arrive as decisions to make, not clauses to interpret: which supplier or customer concentration risk needs a second source, which renewal needs renegotiating, which compliance rider needs a subject-matter expert before the run starts.

Finance keeps the pen. Every extraction is human-reviewable, flagged clauses route to subject-matter experts for sign-off, and no payment or production decision executes without human approval. The system's job is to do the reading and assemble the context - your team's job stays the judgment calls: approve, renegotiate, or escalate. Every approval and rejection is logged for audit purposes and feeds back into the model, which is how classification accuracy improves on your specific contract language over time.