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Iridium

Operate
Operations
New York, NY

AI agents that verify invoices, catch fraud, and run collections for invoice/receivables-finance lenders, layered onto their existing factoring system.

What it is

Iridium sells an operations layer for factoring and receivables-finance companies, lenders who advance cash against unpaid B2B invoices. It integrates into a lender's existing factoring management system without requiring a migration, then automates the manual, fraud-prone steps: verifying invoices are real (catching duplicate or 'double-financed' and phantom invoices), matching incoming payments to open receivables, running collections outreach on configurable cadences, and handling client and debtor onboarding. Its agent stack spans modalities, voice agents that call debtors with relationship history and adapt in real time, browser agents that pull data from debtor portals, and document-comparison models that normalize messy inputs (scanned receipts, spreadsheets, portal data, payment history) into a single judgment of whether an invoice is legitimate and collectible. Founded by Anthony Eden and Preesha Gehlot, both Imperial College London alumni; Eden previously built fraud-detection and credit-underwriting automation for major banks.

Who it's for

Factoring and receivables-finance companies seeking to cut manual verification and collections labor and fraud losses.

Why it's better

  • "No rip-and-replace" model layers onto a lender's existing factoring management system rather than requiring a platform switch.
  • Multi-modal agent stack (voice, browser, document) combines into one fraud and collectibility signal, rather than a single-channel tool.
  • Purpose-built for factoring-specific fraud patterns, double-financing, phantom invoices, not generic AR automation.
  • Founding team has direct bank-scale underwriting and fraud-detection experience rather than being a generalist AI-agent startup entering finance.

Heard on AI for Founders

Iridium was featured in an episode of the AI for Founders podcast. Hear the full conversation.

Listen to the Episode

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