Sterling raises NZ$3.8m to automate finance-team workflows
Sterling, a New Zealand AI startup founded in 2025, has closed a NZ$3.8 million seed round led by trans-Tasman venture capital firm Blackbird. The capital will fund hiring and a push toward larger enterprise customers in New Zealand, Australia and the United States.
The company is building what it describes as an autopilot for finance teams: software that picks up invoices as they arrive, reconciles bank feeds and handles month-end routines autonomously, logging every action and escalating ambiguous decisions to a human reviewer. The platform integrates with existing ERP systems and accounts-payable tooling rather than replacing them, and is already SOC 2 Type II certified.
Founding story and team
Sterling was co-founded by chief executive Nik Wakelin and Ludwig Wendzich, both alumni of notable Kiwi technology companies. Wakelin previously co-founded time-tracking tool MinuteDock and developer-documentation platform Gelato.io before a senior engineering stint at Deliveroo. Wendzich spent close to a decade leading product and design at point-of-sale software company Vend and, following its acquisition by Lightspeed, served as Senior Director of Product Design there. He also worked as a front-end engineer on Apple.com.
The investor list reinforces the "Kiwi ecosystem reinvesting in itself" narrative. Participants include Rowan Simpson and Eliot Crowther, alongside other former employees and founders from Trade Me, Pushpay, Xero and Vend. James Palmer, Principal at Blackbird, said the first time his team saw Sterling clear a month-end workload the commercial opportunity was clear, adding that Wakelin and Wendzich have the domain obsession the category requires.
Early customers include Manukora, Storypark and Echelon. The company has also received a New Zealand government R&D grant, though the value was not disclosed.
Market context and competitive landscape
The autonomous-finance category is crowded with ambition but thin on fully hands-off product. Most AI tools currently sold to finance teams remain co-pilot style: they surface recommendations or draft outputs but still require a human to execute each step. Sterling is positioning itself as a step further along that continuum, with the software completing tasks unattended and producing an audit trail.
Gartner has projected that 90 per cent of finance functions will deploy at least one AI-enabled solution by 2026, creating a large but fragmented buyer pool. That fragmentation is the core commercial challenge: finance leaders are currently evaluating point solutions for accounts payable, expense management, close management and FP&A separately, from vendors including Tipalti, Brex, Coupa and a growing number of AI-native challengers. Sterling's bet is that a single, workflow-agnostic autopilot layer is more durable than any single-function tool.
SOC 2 Type II certification matters materially here. Enterprise and mid-market finance buyers, especially those operating under audit obligations or in regulated sectors, regard that certification as a minimum baseline before deploying any software with write access to financial records. Having it at seed stage removes one barrier during the sales cycle with the larger enterprise customers Sterling intends to target over the next twelve months.
Regulatory considerations
Expanding into Australia will bring Sterling under the Australian Privacy Act and, depending on customer profile, the requirements of the Australian Prudential Regulation Authority for any financial-services clients. A US push will expose the company to state-level data-privacy regimes, FTC guidance on AI transparency, and sector-specific compliance frameworks such as SOX for listed-company customers. Wakelin acknowledged the trust dimension directly, noting that the next twelve months are about proving an AI agent can perform real finance work reliably, with every action logged and explained, to a standard a CFO can take to their board.
The funding puts Sterling on a timeline that aligns with a broader market inflection: enterprises that began cautious AI pilots in 2024 and 2025 are now evaluating which tools they want to standardise on. Named customer wins and independently audited accuracy benchmarks will be the milestones investors and buyers watch next.