The YC Fall 2025 startup, established by a former Agicap GM and a former Apple Pay engineer, transforms screen recordings of finance workflows into computer agents without requiring API integration. 14 Peaks led the funding round, with Cohen Circle and 20VC participating.
The CFO’s software stack is both problematic and limiting. Enterprise finance teams often use a mix of ERPs, CRMs, spreadsheets, email, and banking platforms built at various times by different vendors for different purposes.
APIs between these systems are often incomplete or missing, making finance teams manage the integration gap themselves by manually downloading, reformatting, uploading, and reconciling data across systems to perform tasks that should be automated.
Zalos, a startup based in San Francisco and London that emerged from Y Combinator’s Fall 2025 batch, has raised $3.6 million with the idea that the solution is not a new ERP but a novel agent that operates the existing stack like a human analyst would.
14 Peaks, the Swiss venture capital firm, leads the funding round, with Cohen Circle and 20VC participating. The list of angel investors is notable for its domain specificity: Mike Lenz, CFO of FedEx; Ian Sutherland, CFO of UK business bank Tide; Paul Forster, founder of Indeed; and others with backgrounds in finance software, accounts payable, and enterprise infrastructure.
The technical approach is unusually straightforward. Instead of requiring API integrations or custom connectors, Zalos trains agents from screen recordings of the actual workflows finance teams execute in their current tools.
A billing cycle recorded in NetSuite, a reconciliation process in SAP S/4HANA, or a month-end close in Sage becomes the training input. The agent then replicates that sequence, logging in with credentials, navigating screens, entering data, and handling two-factor authentication, without modifying the underlying system.
Every action is documented in an auditable log, and the platform holds SOC 2 Part II certification. The avoidance of API dependency is a commercial insight: most enterprise automation efforts in finance stall because APIs don’t exist, don’t provide the right data, or require months of integration work before functioning.
The two founders reached the same conclusion from different paths. William Fairbairn, CEO, spent years as UK General Manager at Agicap, a CFO-focused software company valued at about $800 million, engaging in numerous conversations with finance leaders consistently frustrated by ERP implementations: projects that take over a year, offer modest upside when successful, and have real career consequences when they go wrong.
Hung Hoang, CTO, spent five years at Apple, working on Apple Pay’s Buy Now Pay Later product and other AI initiatives, and became focused on computer agents partly through work at Twin, a lab focused specifically on the technology. The two met at Y Combinator and started building Zalos in October 2025.
The market positioning is clear but contested. OpenAI’s Operator and Anthropic’s capabilities operate at the general-purpose level, with agents able to perform tasks across any interface.
Zalos is making a different bet: that finance operations need accuracy levels, audit trails, and domain-specific skills (Excel manipulation, ERP navigation, categorization logic) that general-purpose agents cannot reliably provide. The company’s current customers are in midmarket and enterprise finance teams; it plans to expand into additional enterprise ERPs and on-premise systems with the new funding.