Investing in Maxa:
A huge data opportunity hiding in plain sight
Founders on a mission
A massive problem for the mid-market and the enterprise
CFOs at every mid-market and enterprise company are constantly seeking to better understand the operational and financial performance of their business; which product SKUs are less profitable? Why is my inventory cost higher in certain areas? Why am I paying more overtime in specific teams? The answers to these questions are well hidden within their multiple Enterprise Resource Platforms (ERPs) and other financial and operational systems of record: NetSuite, Oracle, Salesforce, ServiceNow, Quickbooks, SAP... There are thousands of those systems and it is common for an enterprise to use several if not dozens of them.
In order to answer these daily questions, CFOs and FP&A professionals end up spending their days navigating the complexity of multiple systems, extracting complex, disjointed data from several disparate ERPs, and attempting to join them in Excel. This is time consuming, error prone, and incredibly inefficient. ERP providers’ BI and analytics solutions are siloed and proprietary, and don’t move at the speed of business, simply put: it sucks.
Maxa was founded in 2019 to help solve this problem hiding in plain sight. Maxa enables the complete automation of a company's ERP data, across all systems, so that FP&A teams have a single source of truth and can deliver insights in a snap.
Building a magical solution
Maxa automatically unifies multiple ERP and data systems into a data product. A Maxa Data Product is enterprise data that is standardized, made relevant with pre-computed insights ready to be consumed by non-technical users and reusable across tools and algorithms, without the business logic being locked into a visualization layer. All these insights are generated in seconds, not weeks.
It’s all delivered via the Snowflake Data Cloud as a Snowflake Native App. Maxa created the universal enterprise data schema which is essentially an intermediate mathematical language; they built a single data model across ERPs. This allows them to take siloed systems and make their data available in an efficient and unique way to advanced analytics and artificial intelligence models.
Founders on a mission
Raphael Steinman and Alexis C. Steinman are the quintessential founders. Smart, gritty, humble, not afraid to take risks and looking to make a big dent in the world. They just raised a US$21M Series A in which Amiral Ventures participated - we couldn’t be happier. The company is on an incredible trajectory and is poised to become a Canadian flagship.
Why now?
The underpinning of Maxa’s solution depends on storage and compute becoming extremely cheap and infinitely scalable which only really became a reality in the past few years. Their solution hinges on the ability to crunch billions of rows of data in seconds. This allows for Maxa to create massive value for their customers. Their algorithm also becomes highly reusable. Hundreds of templates now become available for all their customers and insights available at the click of a button. In essence, they are trying to make advanced financial analytics a commodity; taking something that used to be really hard and allowing their customers to move much faster and run their business much better.
A scalable and robust model
Success comes from making good decisions (and learning from bad ones). One of the good decisions they made was to not try to reinvent the wheel. Instead of building a reporting front-end, Maxa simply leverages existing tools like Power BI, Tableau and Looker. In the current age of LLMs, this was quite prescient. One of the new opportunities for Maxa is to use this new form of computer communication instead of legacy dashboard reporting. The promise of generative AI only works if the data can be trusted and the single source of truth for companies is their ERP.
Moreover, it’s a usage based business model which is super scalable. Customers get hooked since it solves a major problem and decide to use Maxa for more & more analytics needs (read: strong LTV). Ultimately, this gets people out of crunching data in Excel and frees up executives’ time to work on the business. Demand planning, forecasting, procurement, inventory management all generate tons of data; what’s missing is insights. This is where Maxa excels. For example, live performance per SKU was not imaginable a few years ago. This drives automated insights which can be tied directly to financial impact for their customers. To top it off, their native app captures Snowflake’s capabilities all while protecting sensitive customer data.
The global opportunity
The ERP software market is substantial and rapidly expanding. An estimated $250B is spent on systems each year. it's projected to exhibit a compound annual growth rate exceeding 24% over the next several years. This growth is fueled by the escalating need for operational efficiency, transparency in business processes, and the urgent requirement for data-driven decision-making. There are 4M companies globally running an ERP. Additionally, there is an estimated $1T staff automation cost savings potential with companies increasingly seeking manual task automation. It’s a limitless opportunity for Maxa.
Building the next Canadian Flagship
Maxa demonstrates exceptional potential for growth in a massive global market. Their innovative solution addresses a clear pain point which demonstrably saves an FP&A team significant time while demonstrating rapid return on investment for their customers. This creates a lot of value to their users with a robust and scalable business model. Maxa was also selected as startup of the year by Snowflake as well winning the 2024 Data Driver’s award which has engendered significant customer interest. The founding team possesses both deep industry expertise and a track record of execution, bolstering our confidence in their ability to drive Maxa's success. This combination of product-market fit, scalability, and a strong team positions the startup exceptionally well for rapid growth.
Maxa fits squarely into Amiral’s vertical AI thesis: using innovative data-first technology to create significant customer value. There is a clear imperative for businesses across the world to increase their productivity and we believe that tackling ERP data to derive real-time financial insights is a huge unlock to allow each business to focus on what really matters. It is clear that running LLMs on financial ERP data has huge potential if you can trust the results, and Maxa has demonstrated that running AI on the Maxa universal model provides better results than directly on the ERP’s complex databases.
Congratulations to Alexis, Raphael and the entire Maxa team. You are only getting started!
