Loan Application Pack → Structured Application
Parse application forms, income evidence, statements, and collateral documents into a complete lending data model with derived metrics such as DTI and LTV for faster underwriting.
Use Cases
The same agentic engine supports document intake, structured extraction, policy Q&A, reconciliation, and human approval gates — across regulated and operational domains.
Loan origination, compliance onboarding, and operational controls with auditable agent steps.
Parse application forms, income evidence, statements, and collateral documents into a complete lending data model with derived metrics such as DTI and LTV for faster underwriting.
Normalize identity, ownership, and compliance-critical details from IDs, company filings, proofs of address, and financial statements into auditable onboarding profiles.
Convert waiver discussions and exception memos into structured decision records with rationale, policy references, approvals, and timestamps for regulatory traceability.
Enable staff to ask natural-language policy questions and receive precise clause-backed answers that improve consistency in compliance and customer-facing decisions.
Match external transactions against internal ledgers using amount, date, references, counterparties, and fuzzy text logic to surface breaks and accelerate close controls.
Policy servicing, claims intake, and underwriting submissions standardized for production workflows.
Extract policy headers, coverages, limits, deductibles, territories, and exclusions from schedules and endorsements into structured policy objects for analytics and servicing.
Convert FNOL forms, photos, invoices, and reports into complete claim files with claimant data, policy linkage, loss details, reserves, and line-level support.
Standardize broker submissions into underwriter-ready risk profiles with exposure metrics, loss history summaries, suggested terms, and referral flags based on appetite rules.
Help underwriters and claims handlers query internal manuals and regulatory guidance in plain language with explicit references for governance and quality assurance.
Normalize exposure and claims-history data from mixed formats into standardized tables for portfolio analytics, catastrophe modeling, and pricing workflows.
Close automation, AP/AR processing, and audit-ready exception handling.
Generate proposed journal entries, chart-of-account mappings, variance explanations, and review-ready close notes from month-end inputs such as trial balances, accrual schedules, and invoices.
Extract vendor invoices and supporting documents, validate against purchase orders and approvals, then prepare coding suggestions and posting-ready AP journal lines.
Match incoming payments to open receivables using remittance references, customer mappings, and amount/date logic to accelerate cash application and reduce unapplied balances.
Compare intercompany balances across entities, identify mismatches, and generate proposed elimination entries with traceable support for consolidation close.
Review expense claims and receipts against policy rules, detect duplicates or non-compliant items, and produce exception queues with rationale for finance reviewers.
Process asset acquisition, transfer, and disposal documents to update fixed asset registers, depreciation attributes, and accounting classifications consistently.
IT service management, contracts, CMDB, and operational knowledge at scale.
Convert emails, PDFs, screenshots, and chat logs into normalized ServiceNow or Salesforce case records with category, priority, SLA, affected configuration items, and customer mappings.
Extract signed terms, pricing, line items, obligations, and renewal dates from contracts and statements of work into linked CRM objects for accounts, contracts, and services.
Transform vendor datasheets and inventory files into CMDB-ready configuration item records with normalized attributes such as model, serial, owner, environment, and relationships.
Provide grounded question-answering across runbooks, knowledge base articles, release notes, and procedures so teams can resolve incidents faster with cited guidance.
Classify free-form change, access, and purchase requests, then infer risk level and policy-driven approval chains to reduce misrouted approvals and cycle time.