Incard secures £10m Series A to scale a “financial OS” for high-growth digital businesses

At the ai world organisation, we track funding rounds like this because they reveal where modern business infrastructure is heading and which pain points founders are prioritising next. Incard, a London-based fintech building a unified financial platform for high-growth digital companies, has raised £10 million in Series A funding led by Smartfin, with participation from Founders Capital, MountFund, and angel investors. The funding is aimed at expanding the platform to more markets, strengthening product depth, and accelerating automation and AI-driven workflows while scaling internal teams that matter for financial products—engineering, compliance, and product development.

This raise lands at an important moment for digital-first operators—e-commerce brands, performance marketing agencies, affiliate businesses, and resellers—where growth often outpaces the tooling meant to manage it. Incard was created by entrepreneurs Theo Cesarini, Soraya Tribouillois, Liam Seskis, and Matteo Martino, who set out to solve what they saw as a persistent operational gap: business banking and finance processes for fast-moving digital companies often end up fragmented across apps, portals, spreadsheets, and ad platforms. Incard launched its platform in 2024 with the intent to consolidate core financial workflows and offer a system that can keep up as a company scales in complexity, spend volume, and entity structure.

From the outside, it can be tempting to label this category as “just another neobank.” What makes the positioning different is the product direction: Incard describes its platform as a financial operating system that sits across banking, payments, and financial tools, bringing them into one place and shaping them around how digital businesses actually run. That “OS” framing matters because it implies orchestration (how systems work together) rather than a single feature or a single account—something that tends to be more defensible when a company’s needs evolve month by month.

Why digital businesses outgrow traditional banking setups

High-growth digital businesses don’t just grow revenue; they grow moving parts. A brand can add new sales channels, spin up multiple ad accounts, launch in a new country, manage multiple currencies, open separate entities for tax or operational reasons, and juggle suppliers, creators, agencies, and logistics partners—all in a short window. In that environment, “finance” becomes less about having an account and more about having real-time visibility and control over cash flow, ad spend, payables, and incoming receipts, without relying on constant spreadsheet maintenance.

Incard’s founding thesis is that the legacy approach—stitching together banking, invoicing, spend tracking, and multiple disconnected tools—forces founders to spend too much time reconciling data instead of steering the business. When finance lives in too many places, decisions become slower and riskier: cash flow can look healthy in one tool while liabilities and ad commitments are rising elsewhere, and by the time a team notices, the window to react has narrowed.

There’s also a behavioural reality in digital commerce and performance marketing: spend is often front-loaded and iterative. Teams test creatives, adjust bids, shift budgets, and respond to platform changes quickly, which can push finance operations into a reactive mode. If the finance stack can’t capture what’s happening as it happens, reporting turns into an after-the-fact narrative rather than a control mechanism that supports daily decisions.

This is where a “control layer” becomes a useful concept. If a platform can unify accounts, cards, payments, and analytics—and make that information actionable in near real time—it becomes easier to run a modern digital business with discipline while still moving quickly. In Incard’s case, the goal is not only consolidation, but also workflows and add-ons that reflect specific industry patterns (for example, businesses with high advertising spend, foreign exchange exposure, or multi-entity structures).

For readers who follow the ai world summit circuit, this trend mirrors a broader shift we see across industries: operational “command centers” are replacing isolated tools. Whether it’s marketing ops, supply chain visibility, or customer analytics, companies increasingly want a single pane of glass plus automation that reduces manual work and errors. That same dynamic is now showing up more clearly in finance operations for digital-native companies.

What Incard is building: a unified financial operating system

Incard’s platform brings several core functions into a single interface, including business banking, corporate cards, and connected bank accounts. On top of that foundation, the product concept extends through an app store approach: companies can add tools depending on their industry and stage of growth, which can include invoicing, spend management, treasury, working capital, and other financial capabilities.

The “OS” proposition is essentially a promise of centralization plus adaptability. Centralization means finance teams and founders aren’t constantly exporting and reconciling data across systems. Adaptability means the platform can shift with the business: a company may start with basic banking and cards, then quickly need better invoicing workflows, then add treasury or working capital features as volumes and complexity grow.

A practical way to think about this is to separate three layers. First is the “rails” layer (banking and payments connectivity). Second is the “control” layer (policy, spend visibility, cash flow view, and workflow logic). Third is the “extension” layer (industry-specific add-ons and integrations that make it fit the way a particular business runs). Incard’s positioning suggests it wants to be strong across all three, with particular emphasis on the control and extension layers—where differentiation tends to compound over time.

In the funding announcement context, Incard has highlighted that it is seeing adoption among high-growth digital businesses across the UK and Europe, especially those that operate with high advertising spend, FX exposure, and multi-entity setups. That focus is logical because these are the operators who feel the “fragmentation tax” most sharply: they are often paying multiple vendors, managing fast-changing budgets, and dealing with currency and structural complexity that can make basic reporting surprisingly difficult.

From a market lens, this is also the kind of niche where product-led growth can work well. When a platform makes day-to-day operations noticeably easier—reducing manual reconciliation, improving visibility, and making spend controls simpler—teams tell each other. It becomes a word-of-mouth story inside founder communities, operator groups, and agency networks because the pain is shared and the wins are tangible.

At the ai world organisation, we also watch for one more indicator: whether platforms like this are setting up for “workflow intelligence,” meaning they move beyond dashboards into proactive actions. That is where automation and AI matter—not as buzzwords, but as levers that can compress operational cycles, prevent mistakes, and improve decision quality without adding headcount.

How the £10m Series A will be used: expansion, automation, and AI workflows

With the new Series A capital, Incard plans to expand into additional markets, including deeper moves across Europe and into the US. Alongside geographic growth, the company is planning continued investment in its product offering—particularly its app store concept—and additional investment in automation and AI-driven financial workflows.

The mention of compliance and product development team growth is especially important for any platform operating close to regulated financial services. Scaling into new markets typically means navigating different regulatory regimes, banking partnerships, and operational requirements. When a fintech says it will grow compliance alongside engineering, it’s a signal that it expects real complexity in the next stage, and it’s preparing to build processes rather than patching them later.

On the product side, “automation” in finance operations can range from straightforward to sophisticated. At the straightforward end, it includes automatic transaction categorization, invoice reconciliation, and integration-driven syncing with accounting and commerce tools. At the sophisticated end, it includes policy-driven approvals, anomaly detection, forecast-driven alerts, and workflows that adapt based on spend patterns or cash constraints. When AI is layered in thoughtfully, it can move teams from manual checking to exception management—where humans focus on the few cases that need judgment.

For high-growth digital operators, this matters because their finance workload does not scale linearly. A small increase in volume can create a large increase in operational noise: more transactions, more vendors, more refunds, more ad payments, more currency conversions, more entity-level reporting requirements. If automation can reduce repetitive work, the business can scale without finance operations becoming the bottleneck.

This is also where the app store approach can act as a distribution mechanism for specialized workflows. If a platform can let companies plug in the exact tools they need—without rebuilding the entire finance stack—it becomes more resilient to change. That matters in digital markets where business models shift quickly and platform dynamics (ad channels, attribution, payment methods, consumer demand) can change within a quarter.

In other words, the Series A is not simply about adding users; it’s about building a product and operating model that can support more sophisticated customers, more regulated contexts, and more complex financial realities. For anyone attending the ai world summit 2025 / 2026, this is a useful case study in how verticalized platforms are winning by combining a tight customer focus with deep operational capability.

What this means for e-commerce brands, agencies, affiliates, and resellers

For many digital businesses, finance has traditionally been treated as “back office.” Yet the fastest-growing operators increasingly treat finance as a growth function because it directly governs how confidently they can deploy capital—especially into advertising, inventory, and expansion. A platform like Incard is essentially competing on one promise: turning financial operations into a real-time control center rather than a retrospective report.

If you run an e-commerce brand, the immediate value is usually clarity and speed. Clarity means you can see where cash is going, how ad spend relates to revenue outcomes, and whether working capital is tightening before it becomes a crisis. Speed means decisions aren’t delayed by reconciliation cycles, scattered tools, or manual reporting workflows. When these improve, planning becomes more accurate, and teams can take calculated risks with better guardrails.

If you operate an agency or manage performance budgets across clients, the need often shifts from “single company finance” to “multi-context finance.” You care about spend visibility and controls, but also about how quickly you can separate, track, and understand flows without drowning in operational overhead. Even when agencies aren’t directly managing a client’s banking, they live inside the consequences of financial opacity: slow approvals, unclear budgets, delayed payments, and planning friction.

Affiliates and resellers, meanwhile, often face a different complexity profile—fast-moving revenue, variable margins, multiple payouts, and the constant need to reinvest. Real-time visibility into cash flow and spend can directly influence how aggressively they can scale, especially when marketing spend and inventory decisions need to be made quickly.

Incard’s reported adoption among companies dealing with high ad spend, FX exposure, and multi-entity structures points to a very specific kind of customer maturity. These operators already know the operational cost of fragmentation, and they are actively searching for systems that can keep up. For them, the “best” finance platform is less about a shiny feature list and more about whether it reduces complexity, increases control, and improves decision speed.

From a broader ecosystem perspective, this also highlights a trend we frequently discuss at the ai world organisation: category convergence. Banking, payments, spend management, and analytics are no longer separate purchasing decisions for many modern companies. They’re becoming part of a single operating layer, often with industry-specific packaging. As competition intensifies, platforms will differentiate through deeper integrations, smarter workflows, and better operational outcomes rather than simply offering an account and a card.

Why this funding round matters for the AI + fintech roadmap

Even though the headline is a funding round, the deeper story is about how financial operations are being redesigned for digital-first business models. The phrase “AI-driven financial workflows” should be interpreted carefully: AI is not a replacement for finance leadership, policy, or compliance discipline. It is a mechanism for scaling decision support and automation—helping teams catch issues earlier, reduce manual work, and operate with more precision.

As fintech platforms move toward “operating systems,” they will face three persistent challenges. The first is trust: when money is involved, reliability and predictability matter, and customers need confidence that automation won’t create hidden errors. The second is regulatory and operational resilience: expansion across markets multiplies complexity. The third is outcome clarity: platforms must show they are improving business results, not just adding dashboards.

This is where a well-executed product strategy can compound. If Incard can keep its promise of centralization, extendability, and real-time control while scaling into new markets, it positions itself as a core system of record for a certain kind of digital operator. And if it can translate automation and AI into measurable time savings, better cash discipline, and faster decision cycles, it becomes more than a fintech product—it becomes operational infrastructure.

For founders and operators watching this space, it’s also a reminder that “finance tooling” is now a competitive advantage. Better visibility and control can influence how quickly you can scale, how safely you can take risk, and how effectively you can deploy capital. In tight markets, that can be the difference between growing sustainably and hitting preventable constraints.

At the ai world summit, we regularly explore how AI is reshaping real business functions—not in demos, but in daily operations. Incard’s direction fits that theme: applying automation and AI to reduce friction in a high-stakes, high-frequency workflow environment. If your business touches performance marketing, cross-border payments, or multi-entity operations, the rise of finance operating systems is not an abstract trend—it’s a practical response to how modern digital businesses actually work.

As the ai world organisation continues to curate ai world organisation events and ai conferences by ai world, we’ll keep spotlighting these “infrastructure shifts” because they’re often leading indicators. Today it’s finance operations; tomorrow it’s procurement, risk, and compliance automation; and across all of it, we’ll see more intelligence built directly into workflows. If you’re building, buying, or partnering in this space, the conversation belongs at the ai world summit 2025 / 2026—where operators and innovators can compare notes on what’s working, what’s hype, and what’s next.