Risk Ledger, a London-based supply chain security firm, has raised £24 million (roughly $32.3 million) in a Series B funding round, bringing its total funding to £33.8 million (about $45 million). The round was led by Axiom Equity, with participation from existing investor Mercia Ventures.

Founded in 2018, Risk Ledger operates a network-first platform designed to address third-party and supply chain cyber risk. Rather than relying on one-off point-in-time assessments, the platform connects organizations and their suppliers so that supplier profiles are built from standardized assessments and kept updated in real time. The company describes this model as a shift toward what it calls Active Supply Chain Security, an approach intended to help organizations collectively defend against systemic risks that ripple across shared vendors and partners.

Risk Ledger says more than 16,000 organizations have joined its network, spanning financial services, critical national infrastructure, government, and insurance sectors.

Where the Funding Goes

The company plans to use the new capital to:

  • Expand the number of organizations connected to its network
  • Deepen the intelligence and risk signals shared across the platform
  • Build additional AI tools to automate supplier reviews and surface risk indicators
  • Expand operations into the United States

Jonathan Organ, founding partner at Axiom Equity, framed the investment as a bet on network effects rather than a crowded vendor market. He said Risk Ledger is building a category of its own, one where the network becomes harder to replicate and more valuable as additional organizations join. He also pointed to the company’s traction with what he called serious customers as evidence of product discipline.

The raise adds to a string of recent cybersecurity funding announcements, reflecting continued investor appetite for platforms that combine risk intelligence, automation, and AI-assisted analysis. For security teams managing sprawling vendor ecosystems, the growth of network-based assessment models signals a broader industry shift away from static, point-in-time third-party risk reviews toward continuously updated, shared risk data.