AI helps due diligence teams rapidly synthesize information like financial health, ownership,legal exposures, customer traction, and technology risks, while grounding each insight to realsource documents.
This reduces manual review time and improves diligence consistency.The RAG assistant can generate diligence memos, highlight red flags, and suggest follow-upquestions, all of which help improve decision-making.
Scenarios
Investment Diligence: A corporate investment arm evaluates purchasing equity in a company that offers identity verification. The RAG assistant reviews financial statements and cap tables, scans legal documents for obligations, and summarizes architecture docs for security posture and risk. It produces a diligence memo and a prioritized list of questions for management.
Benefit: consistent diligence coverage across deals, improving decision making while reducing the chance of late-cycle surprises in legal, security, or financial terms.
Vendor Diligence: A company considers purchasing from a claims automation vendor and needs to understand integration and operational risks as early as possible. The RAG assistant analyzes the vendor’s documentation against the company’s existing processes to identify dependencies and scalability limits. It further reviews legal documents for IP and SLA obligations and scans customer references for product fit and churn risk.
Benefit: better roadmap planning and contract discipline, with early insights for executive decision makers and ongoing insights for integration team members.
Lending Diligence: A commercial lender is underwriting a growth-stage borrower with limited historical data and several complex contracts. The RAG assistant summarizes the borrower’s financials, focusing on revenue concentration, and flags restrictive terms or change-of-control clauses while citing the underlying legal documents.
Benefit: a more complete credit memo, quicker turnaround, and better alignment between credit, legal, and risk on key downside scenarios.
Scenarios
Guided Dispute Resolution: A customer calls to dispute a fee and asks whether it can be waived. The assistant retrieves the relevant fee schedule, the product's terms and conditions, and any policy exceptions for hardship or relationship tiers. It drafts a support agent response that explains the fee, outlines waiver eligibility, and documents the decision path.
Benefit: faster support resolution with improved fairness and auditability in how fees are applied.
Support Agent Knowledge Base: A customer cannot complete a mobile transaction and contacts a support agent via chat. The agent asks the RAG assistant to guide troubleshooting based on the knowledge base and FAQ. The RAG model proposes the next best step and, when needed, an escalation script for the agent.
Benefit: higher first-contact resolution and faster digital issue handling, reducing support volume and customer frustration.
Supporting Policy Changes: The organization updates a policy (e.g. a timing or contractual change) and support needs to answer customer questions immediately. The RAG assistant retrieves the updated policy documents, revised FAQ, and any updated terms, then generates a consistent explanation for agents and customers.
Benefit: rapid propagation of change across channels, reduced misinformation, and assurance that customers receive the latest official information.
Deliver AI workflows that help your team move beyond the hype. Share your details to get started.