The YC Fall 2025 startup, founded by a former Agicap GM and a former Apple Pay engineer, converts screen recordings of finance workflows directly into computer agents, no API integration required. 14 Peaks led the round, with Cohen Circle and 20VC participating.
The CFO’s software stack is both the problem and the constraint. Enterprise finance teams typically run on a combination of ERPs, CRMs, spreadsheets, email, and banking platforms that were built at different times, by different vendors, for different purposes.
APIs between these systems are often incomplete or absent, which means finance teams absorb the integration gap themselves, manually downloading, reformatting, uploading, and reconciling data across systems to complete tasks that should be automated.
Zalos, a San Francisco and London-based startup that emerged from Y Combinator’s Fall 2025 batch, has raised $3.6 million on the thesis that the fix is not a new ERP but a new kind of agent that operates the existing stack the way a human analyst would.
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The round is led by 14 Peaks, the Swiss venture capital firm, with participation from Cohen Circle and 20VC. The angel list 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 direct. Rather than requiring API integrations or custom connectors, Zalos trains agents from screen recordings of the actual workflows finance teams run inside their existing 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 a username and password, navigating screens, entering data, handling two-factor authentication, without any modification to the underlying system.
Every action is captured in an auditable log, and the platform holds SOC 2 Part II certification. The avoidance of API dependency is the commercial insight: most enterprise automation efforts in finance stall because the APIs don’t exist, don’t expose the right data, or require months of integration work before anything runs.
The two founders arrived at the same conclusion from different directions. William Fairbairn, CEO, spent years as UK General Manager at Agicap, a CFO-focused software company valued at around $800 million, where he had hundreds of conversations with finance leaders whose consistent frustration was ERP implementation: projects that take more than a year, deliver modest upside when successful, and carry 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 began building Zalos in October 2025.
The market positioning is clear but contested. OpenAI’s Operator and Anthropic’s computer use capabilities both operate at the general-purpose layer, agents that can perform tasks across any interface.
Zalos is making a different bet: that finance operations require accuracy levels, audit trails, and domain-specific skills (Excel manipulation, ERP navigation, categorisation 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 capital.
