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Harish is providing the Amazon Prime fulfillment experience to everyone else through a combination of AI and an asset-light network of warehouses across the United States.

Alex is automating workflows for the world’s largest enterprises by using process mining to build the connective tissue for businesses.

Mayan is delivering Autonomous IT to the largest companies in the world through systems of intelligence.

Carsten built one of the largest commerce platforms in the world, which powers enterprise merchants and retailers across the globe and now serves as the SAP commerce engine.

Soups is stopping financial crime in its tracks by building the first end-to-end platform for fraud, risk, and compliance.

Adam is enabling restaurant owners to take back their customer relationships by digitizing their entire online and offline operations in a single platform.

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Activant is a research-led global investment firm that partners with high-growth companies.

We partner with founders who have won their initial battles and are ready for the next challenge.

We typically invest when two things come together. First, the company has the potential to achieve escape velocity and transform an entire industry. Second, we believe the founders can lead the company through hyper growth, and our support can significantly increase the probability of this success. 

The critical time window to escape competitors and transform an industry is not open for long.

That’s why after we invest, the real work begins.

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We only partner with a few founders per year. But when we do, we’re fully committed.

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Raised by two Italian immigrants, Matilde grew up in a bilingual and bicultural home where she developed a deep love of learning and problem solving. 

Matilde started her career with an internship at Goldman Sachs as one of two Sophomores selected to join the TMT group. Once she returned post-grad, she spent her time focused on internet and commerce companies. Matilde has experience in managing complex financial transactions, such as private placements, IPOs, and M&A processes. 

Matilde joined Activant to further feed her curiosity and finds it energizing having the opportunity to meet the people who are building the future.

“There is nothing more satisfying than cracking a complicated puzzle or problem, it becomes all consuming. As an investor, you are repeatedly solving puzzles, whether that’s making sense of disruptive technologies or breaking down entire industries. At Activant, I have the opportunity to solve these puzzles alongside an incredibly supportive team that challenges my assumptions and makes learning exciting.”

Goldman Sachs is a leading multinational investment bank and financial services firm.

B2B transactions made up 97% of the ~$156 trillion in cross-border payment flows i

 and, according to UBS estimates, took 2-5 days to settle at an average cost of 

 This is incongruous in a world where real-time payments (RTP) are transforming the payment landscape, particularly in domestic markets in developing economies (like Brazil and India), with settlement times decreasing to seconds and costs reduced by 50-90%.

The global payments market recorded revenues of $2.2 trillion in 2022, an all-time high and up 11% for the

 With the notable exception of China, where payment revenues declined 3% in 2022, all other regions globally (North America, Latin America, Europe, Middle East, and Asia ex China) grew at double-digit ra

 About half of this revenue growth came from rising interest rates, but fees still make up more than half of all payment 

 When one considers that domestic payments cost anywhere between 30bp and 300bp depending on the payment rails used (ACH or card), and international payments costs (excluding foreign exchange fees) range from 65bp to 

 there is a significant profit pool to be disrupted.

Online payment platforms Square and Stripe used technology to bring innovation, convenience, and efficiency to sleepy local payments markets. They, and other payment facilitators (payfacs), have opened markets to many more merchants, lowered costs for everyone, and introduced a wide array of products and services that allows them to monetize payment flows. These offers range from hardware (like 

) to related software (such as Stripe’s 

 products). We have also seen the rise of payfac-as-a-service (PFaaS) solutions to allow non-fintech companies to offer payment acceptance to their customers. Shopify, for example, is powered by 

Payfacs disrupted payments markets by overlaying technology and services onto existing payment networks (or rails). Real-time payments, however, are disrupting markets around the world using an entirely new set of rails.

Real-time payments (RTP) are account-to-account (A2A) financial transactions that are initiated, cleared, and settled immediately–typically within seconds. These payments run on RTP networks, which both central banks and commercial banks have designed to connect financial institutions and enable them to offer faster and cheaper payment solutions to consumers and merchants outside of traditional payment infrastructure or rails (cash & check, ACH, wire, card).

The first RTP network was launched in Japan in 

 but it is only over the past five years that growth has exploded. Today, there are over 80 RTP networks operating around the world that accounted for 195 billion transactions in 2022 (18% of all global electronic payments 

 ACI estimates that this market will grow at a compound annual growth rate (CAGR) of 21% to reach 512 billion transactions by 2027, representing 28% of all payments transactions. Most of this growth will come from EMEA (21% CAGR) and Latin America (29% CAGR).

Emerging economies such as India and Brazil account for the majority of RTP transactions. These two countries alone represented ~61% of global RTP transactions in 

 India launched their RTP network, Immediate Payment Service (IMPS), in 2010 but it was only in 2016 that growth really exploded with the rollout of their Unified Payments Interface (UPI). The system enabled real-time payments across numerous channels (P2P, C2B, B2B, and C2G) through mobile numbers, QR codes, and virtual 

 In 2022, UPI facilitated ~90 billion transactions representing ~45% of all transactions in 

 Brazil’s PIX instant payments network is driving a similar change in that country, as is the NIP system in Nigeria where cash transactions fell from 95% in 2019 to 80% in 

Developed markets have been slower to adopt RTP networks, with Europe and the U.S. processing only 13 billion (7% of all transactions) and 4 billion (2% of all transactions) transactions respectively in 

 The U.S. has three established RTP networks: The Clearing Houses’ (TCH) RTP network, Early Warning Services’ Zelle mobile peer-to-peer instant payment application, which both launched in 2017, and most recently the Federal Reserve Bank’s FedNow, which launched in 2023. TCH’s RTP network has seen a significant increase in growth after a slow start, with 2Q23 volumes representing a 5.8x year-on-year (YOY) increase. Zelle, on the other hand, has seen substantial growth since launch and is the clear leader in terms of P2P real-time payments. Zelle is owned by a consortium of large U.S. banks that guarantee distribution by providing easy access for their large customer bases.

RTP currently represents 12% of all credit transfers in the Single Euro Payments Area (SEPA) and McKinsey estimates this share could double by 2027, or even increase four-fold to ~45% of payments transactions if regulators pass anticipated legislation to encourage adoption of 

RTP will undoubtedly grow to become the preferred payments option in countries around the world. The benefits of RTP networks and transactions are real and compelling. They offer:

as interchange fees are reduced or bypassed entirely;

 by enabling bi-directional communication in a secure system, introducing two-factor (or multi-factor) authentication, and device binding and confirmation;

 by conforming to ISO20022 (which enables financial institutions to send data-rich sets with each transaction);

 into financial positions, reducing the risk of overdraft fees or other penalties,

by expediting refund and disbursement processes; 

 that customers appreciate, like QR payments, split payments, or request-to-pay options.

As one considers the many benefits of RTP, it is important to recognize that all real-time payments are irrevocable and can’t be reversed or “de-authorized” by the payor, which places a premium on fraud and risk management.

Against this backdrop of widespread adoption and very encouraging growth, it is interesting to observe that this has largely been driven domestically, while most payment volumes are cross-border and B2B.

Cross-Border Payments Offer a Unique Opportunity

Cross-border payment flows continue to grow at double-digit rates, generating $240 billion in revenues for payments providers in 2022, with B2B payments making up 69% of total revenues (on 97% of the payment 

 Consumer payments are more profitable and are projected to grow more rapidly over the next 5 

 The U.S./Latin America corridor, the largest in the world for C2C remittances, is expected to continue growing robustly given family remittances and U.S. humanitarian 

Despite the volume of capital flows and benefits that RTP could bring, cross-border payments continue to operate on traditional rails or networks designed to handle wires, credit and debit cards, and international ACH transactions. These traditional networks are:

, with wire and card transactions taking 2-5 business days to settle;

 than new networks operating to the ISO20022 standard as the messaging format of legacy rails provides little information regarding transactions;

 as the long settlement times limit visibility into true liquidity positions.

The diagram below illustrates some of these disadvantages by providing an overview of the current cross-border payment process flows, the associated costs, and average settlement times.

Incumbent Cross-Border Transaction Process Flow

RTP networks have the potential to address all the issues identified, just as they do in local markets, by linking domestic networks across borders. Singapore connected its PayNow service with Thailand’s Promptpay system to launch the first true cross-border RTP network, and later linkedPayNow with India’s UPI service. The Bank of International Settlements Innovation Hub (BISIH) launched its Nexus project in 2022 and built a working prototype to connect the test systems of three established RTP networks – the Eurosystem’s TARGET Instant Payment Settlement (TIPS) system, Malaysia’s Real-Time Retail Payments Platform (RPP), and Singapore’s Fast And Secure Transfers (FAST) system– across borders. Similarly, the Immediate Cross-Border Payments (IXB) pilot was launched as a collaboration between U.S.-based TCH and Europe’s

 The pilot linked TCH’s RTP network in the U.S. with ECB Clearing’s RT1 network to process $:€ transactions and was designed to add additional currency corridors after the planned commercial rollout in 2023.

To date, however, no major trading corridors have implemented a commercial solution. Imagine if FedNow, the U.S. Federal Reserve’s real-time payment rail network launched in July 2023, were to link to Brazil’s PIX network to facilitate RTP flows between those countries.

Theoretical Cross-Border RTP Network Process Flow

The FedNow rails are not a finished product and currently aren’t interoperable with other networks, but with this functionality FIs could deliver fast, cheap, data-rich, and transparent cross-border transactions. The large-scale adoption of cross-border B2B RTPs will, however, be limited in the short-term by the need to align:

regulatory frameworks as each country has unique frameworks, data laws, security requirements, and consumer protection laws that need to be adhered to;

interoperability standards between networks in different countries. The global move to the ISO20022 messaging standard should help alleviate this;

settlement systems, as real-time payments require systems that can handle multiple currencies concurrently. These systems vary from country to country;

fraud/Anti-Money Laundering (AML)/Know-Your-Customer (KYC) requirements to handle real-time transactions that are irreversible. Fraudulent transactions made up ~79% of the 1.52% of all B2B transactions charged back in 

financial institution liquidity systems to handle immediate settlements 24/7/365.

We found it helpful to think about the RTP market as consisting of five distinct layers:

RTP Market Landscape

The primary and overlay service players utilize the infrastructure of the connected RTP networks to provide value-added services such as payment processing, remittance, treasury management, and KYC/AML/fraud detection. We see the increased adoption of cross-border RTPs as a net positive for many of the primary and overlay service providers. However, the one specific service area that we believe would be under threat from the growth of cross-border RTP is the remittance and international payment processing businesses. If central banks can successfully connect through cross-border networks and process transactions cheaply, the business case for low-cost remittance and international payments would fall away.

Our Activant Thesis Map, shown on the next page, summarizes our market growth conviction and the degree of technological innovation for each of the distinct clusters of companies. We are most excited about the growth prospects of RTP infrastructure providers and the overlay service providers that build on or enable RTP transactions. These sectors are shown in green on the thesis map. We believe that RTP networks will grow and take market share away from many of the current payment rail systems, but these are often national solutions developed by central banks (like FedNow in the U.S.) or networks of banks (like the Zelle network in the U.S. or the European Payments Initiative in Europe) so we excluded them from consideration. Similarly, we believe that the FIs holding the primary account relationships will benefit at the expense of remittance and cross-border payments players if they offer RTP options that are competitively priced.

Real-Time Payments

We identify promising opportunities among infrastructure players and the providers of overlay services:

Domestic and Cross-Border RTP Infrastructure players are responsible for creating the back-end technology that connects the banks to RTP networks, and RTP networks across borders in some instances. While there is a use case for domestic RTP transaction facilitators like 

 and others, the real margins come from cross-border transactions. As spreads are reduced on domestic transactions, going global presents the opportunity to target profit pools that generate billions in net revenue for incumbent operators.

 and other new entrants targeting this market stand to benefit from increased transaction flow across RTP rails.

Traditional Core Banking Systems and infrastructure players like 

 all provide access to RTP networks, but they aren’t focused on the future of RTP and RTP connectivity in the same way as the RTP infrastructure players.

AML/Fraud Detection is critical and likely to become even more so as fraudsters target the opportunities for instant settlement and the ability to rapidly move money from account to account. B2B transactions, and particularly those that are cross-border, are larger than C2C and C2B payments and typically require increased transaction verification and supplier identification. According to the 2019 Federal Reserve Payments 

 the average B2B ACH and wire transactions were $9,000 and $4.5 million, respectively. This compares to average C2B ACH and wire transaction sizes of $719 and $119,000, respectively. The average cross-border wire transfer was $3.8 million. As a result, there is a clear need for sufficient AML and fraud detection capabilities working alongside the fast and efficient RTP network. Activant is an investor in 

 and others offer interesting and effective solutions.

Overlay Services built to provide solutions addressing a myriad cash and payments related needs – from AR/AP automation to Treasury Management and Payments Orchestration – offer opportunities to improve the efficiency of payment flows through connections to RTP networks. Activant is an investor in 

 unified payments platform that includes connections to FedNow and other RTP networks.

Open Banking APIs were an important catalyst in the proliferation of real-time payments. 

 and other cloud-native aggregators helped broaden the adoption of data sharing, but ultimately these aggregators are not payments companies. These players lead in account information services, but they are not the ones responsible for real money movement. 

Embedded Finance applications also stand to benefit from connections to RTP networks. Many B2B transactions are financed through some form of credit (lease, term loan, or revolving facility). The Equipment Leasing & Finance Foundation reported that ~62.5% of equipment and software investment volume in 2022 was financed (or ~81.5% if credit cards were included).23 Immediate settlement would save the payors interest charges on outstanding balances, potentially increasing the volume and frequency of embedded finance transactions. Activant is an investor in 

 would likely also be net beneficiaries of this improved payment method.

We are confident that RTP offers a step-function increase in benefits over traditional payment options (ACH, card, and wire) and will grow to become the preferred solution in markets around the world. This transformation will likely continue primarily in domestic markets in the short term but will really take off when cross-border payments can be remitted on RTP networks connecting the world’s major payment corridors. Infrastructure players connecting FIs to RTP networks are essential enablers, and a host of new companies providing overlay services will rise to prominence. We are excited about the opportunities that this transformation will create.

If our work resonates, if you're building in the space, or if you have a different perspective, please reach out!

Real-time Payments

It's Time Local Went Global

In 1908, Ford unveiled the Model T, a four-cylinder, 20-horsepower car that cost $850. Production was painfully slow, with factories only able to make ~32,000 per year by 1910.

However, Ford cracked the code on something no one else had solved: part interchangeability.

 This innovation, followed by the introduction of the assembly line in 1913, which broke tasks down into smaller, specialized jobs, cut the average task cycle time for a Ford assembler by an order of magnitude, from 514 to 1.9 minutes.

The result? Just a few years later, Ford had increased the output of Model Ts by a whopping 23x and cut its price by more than half - a tectonic shift that single-handedly launched the automotive age.

Ford's methods continued to define manufacturing, with future waves building on the system. Lean manufacturing, for example, honed in on waste and inefficiency and gained popularity in the 1950s via its success at Toyota.

 In the 80s came Six Sigma, which brought an obsessive focus on quality - with managers using statistical analysis to greatly reduce variation and defects.

But recently, we’ve hit a wall. The progress Ford began over a hundred years ago has largely stalled:

even if a factory has 21st-century machinery, it’s often still managed using 20th-century methods.

We believe that’s all about to change - and not a moment too soon. In this piece, we explore the transformative potential of industrial intelligence, and how it's (finally) poised to drive the next wave of efficiency and sustainability in manufacturing.

Industrial Intelligence is the sub-sector of Industrial software that leverages enterprise data to add an 

to industrial operations. It’s the application of new technologies, like

 modern data infrastructures, analytics, machine learning, and digital twins 

to the industrial sector. Industrial Intelligence means unlocking all the operational data that these organizations generate and leveraging it to drive efficiency, increase returns, and meet sustainability targets.

At this point, you must be asking yourself – how have the world’s leading manufacturers not innovated on their technology infrastructure already? Let’s dive in.

Like many “old economy” sectors, the industrial space has largely been left behind by the past decade of software innovation. Here’s why:

Buying cycles are on par with government procurement (read: glacial). 

Industrial firms often require lengthy proof of concept programs before making a buying decision. Even if ROI is proven, there’s still a bidding process, which further harms success rates. Only a few can stomach the wait - or the risk.

Niche manufacturers have less incentive to innovate. 

If you’re the manufacturer of a particular spring used in a seatbelt retractor for a Porsche 911, odds are you have very little competition. Without competition, the status quo is fine.

Complex manufacturing environments need complex implementations. 

Every customer has a unique combination of legacy infrastructure and future needs. Combine that with a byzantine and often incompatible manufacturing hardware landscape, and you quickly realize why adding a software layer is so difficult.

is an oft-repeated mantra, and for good reason. On average, switching off just a single BMW factory for only one day could cost ~$12mn.

remains a challenge. Telling a tenured production manager who “has been doing this for 30 years” that there might be a better way is never easy, especially when historic “buzzy” areas of manufacturing innovation failed to prove value until now, like 3D printing in the early 2010s.

Taken together, it's no surprise industrial software has come up short - with real costs to companies and consumers alike. 

 Why, you ask? For starters, the companies developing it are not software-natives. Of the top 15 incumbents, 

 - (Dassault, Autodesk, PTC & Ansys). The rest (Siemens, etc.) are hardware players at their core, with software contributing less than 10% of their revenue.

The quality of experience we’ve come to expect from consumer and now business software is hard to come by in the industrial sector:

Nevertheless, many incumbents realize the value of diversifying to recurring, high-margin software earnings in what is historically a cyclical sector - and they have the pockets to go shopping. Rather than develop products organically, many larger players are building out vertical-specific software offerings via acquisitions. Since 2021, for example, Siemens spent ~$2b on buying predictive maintenance tools, while Emerson and Schneider acquired industrial software giants AspenTech and Aveva for ~$11b and ~$10b, respectively.

 This inorganic approach of legacy vendors creates two major pain points in the industry:

For instance, Rockwell’s Design software suite consists of seven different sub-products, among which two were acquired (Emulate3D & Arena) and one accessed via partnership (FactoryTalk Twin Studio).

Complex offerings make plug-and-play extremely difficult. 

Instead, they require significant customization to roll out. Incumbents advertise this “flexibility” as a “feature”, but most operators hate the need to call their service provider for every small change (and the ensuing bill).

 industrial software needs to solve industrial-scale issues

. For one, analyze immense volumes of data: manufacturing plants generate twice as much data as any other vertical.

Per week, a typical smart factory generates ~5PB

 (that’s petabytes, or one million gigabytes).

Throw that at your average legacy software, and more issues quickly come into focus:

Complex infrastructure is fertile ground for data siloes. 

Across the board, experts mention that data often remains stuck on the production-line level. This leads to incomplete (meta-) data, duplicate processes, and barriers to collaboration. Most importantly, however, it hides operational insights - or in other words, better ways to run the factory. In a survey of 1,022 respondents, 

68% reported that data siloes have a negative impact on their work

. Those workers were found to spend 11.6 hours per week searching for the information they needed.

Engineers lack the tools to move right into analysis. 

Data engineers still spend around 40% of their time on data quality – time spent not solving problems.

 We routinely hear of engineers still exporting data from faulty machines to Excel, only to spend days wrestling with it.

Once you get to the analysis, doing it manually is grossly insufficient. 

Manufacturing processes generate immense volumes of data. Finding issues can be like searching for a needle in a haystack – that’s why human analysis will always be too late to be truly impactful. 

Robert Göbel, Co-founder & Managing Director, Spread.AI

In short, there is a massive opportunity to challenge incumbents’ complexity and unlock the insights hidden in operational data - by offering software that is quicker to deploy, easier to customize, cloud-native, and collaborative.

With improved intelligence tools, manufacturers can reduce downtime, improve quality, and increase throughput – aka increase profitability. And crucially, the technical underpinnings for this shift have finally fallen into place.

In the past decade, we have seen three key technologies reach maturity: namely, our ability to collect, store, and analyze data on an industrial scale.

Let’s start with data collection. In 2004, an average IoT sensor cost $1.30. By 2020, the cost had fallen by almost 4x to $0.38.

 IoT has benefitted from the relentless innovation in semiconductor technology & connectivity protocols, driving down costs and improving performance. We don’t expect this trend to slow anytime soon - if anything, just the opposite. 

As IoT sensors multiply, so too will the volume of operational data available to manufacturers.

 are supporting the infrastructure of this significant tailwind with their MQTT platform, which allows customers to send and analyze data from IoT devices in real-time and even manipulate data in motion to ensure integrity and quality across deployments.

Or consider storage. Just years ago, these new flows of data would’ve overwhelmed the average data center. But since 2010, the cost of cloud storage has roughly halved, and the

 number of industrial firms who have completed a shift to the cloud has risen from 13% to 64%.

Now, it is finally feasible (and cost-effective) for manufacturers to store this data for later use.

improvements in database technology open the door for effective analysis. 

 are key to handling the mass of time-series data produced by industrial firms, especially 

. Moreover, as industries increasingly embrace electrification and software-driven "smart" products, graph databases have become instrumental in understanding the interrelationships between mechanics, electronics, and software.

Finally, data analysis has also benefited from rapid advances in processing technology like the 

data warehouse, which has greatly reduced both latency and cost

. A prominent example is Snowflake, which has recently introduced a vertically designed 

Taken together, these technologies finally make possible a “single pane of glass” through which industrial organizations can monitor and analyze their operations in real-time. 

This is the value of true industrial intelligence – it makes data accessible, paving the way for value creation via analytics, machine learning, and digital twins.

Many industrials are facing a steep knowledge cliff: 75% of machine operators in the US are over the age of 45, yet the average 18-year-old does not consider manufacturing as their first-choice career.

 As staff retire and companies lose critical expertise, intelligent software will have to step in. 

The burden of running a factory must shift from accumulated experience to mathematical models

And in a Western world short on skills, the demand for reshoring just adds fuel to the fire. In the US, reshoring-linked jobs are skyrocketing – up 6.5x from 2012 to 2022.

Add geopolitical tensions, the lingering effects of Covid-19 or the 

, and you see why solutions are so desperately needed. 

Estimates are that organizations will need to spend ~$60b to rebuild supply chains in the coming years

Critically, software can also play a key role in our journey to net-zero

. Until recently, for example, Unilever’s Indaiatuba plant in Brazil (which makes powder detergent) was their largest greenhouse gas emitter. By applying machine learning to the spray-drying process, however, the company was able to reduce GHG emissions by 96%.

In fact, the average company applying these technologies sees improvements not just in energy use (-24%), but also in productivity (+52%), labor costs (-32%), and manufacturing costs (-26%).

The scale of the opportunity, both ecologically and economically, is massive. 

In our analysis, we assume that the global manufacturing sector could save ~25% of its COGS, in line with the examples seen above. The resulting resource savings would be equal to the entire GDP of France.

Moreover, savings are only one side of the equation. Efficiency gains are a huge resource unlock, and it's 

impossible to put a number on the upside potential inherent in giving engineers more time to focus on building great products. Our estimate: It will be big, given the sheer size of this industry. 

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