Key Stats: Axle.ai on Republic
Number of Investors
|Likelihood of Max|
The Axle.ai team has been selected as a “Top Deal” by KingsCrowd. This distinction is reserved for deals selected into the top 10% of our due diligence funnel. If you have questions regarding our deal diligence and selection methodology please reach out to email@example.com.
Fueled by the global rise of video as a preferred communication medium of choice, enterprise clients around the world already spend roughly $10 billion each year on video-content management solutions — a market that’s expected to continue growing at a healthy 10% annual clip for the next several years. While a significant portion of that total is reserved for related hardware storage products, the majority — more than 70% — is being allocated toward innovative, higher-margin video-content management software solutions.
It might seem an impossible task for relatively small start-ups to muscle their way into such a well-established, highly competitive space. However, there are still clear shortfalls to the industry’s existing solutions for professional media teams of all sizes. Many such products tend to be highly specialized and are often prohibitively expensive, costing upwards of $50,000 or more. Even then, few effectively address the daunting tasks of searching, organizing, and truly understanding the information contained in the world’s growing hordes of high-quality video content.
As a result, with a lack of useful digital context in their files, many media teams spend inordinate amounts of time searching for or even recreating video content they’ve already made. The industry needs software solutions that can more seamlessly solve these problems at a reasonable price.
That’s where Axle.ai’s three core products come into play.
First, supported by cutting-edge artificial intelligence and machine-learning algorithms, the company’s namesake axle ai software is capable of autonomously searching, tagging, and managing video media through an intuitive browser interface. Much to the delight of its more than 600 clients, axle ai doesn’t require migrating existing media libraries to a proprietary file system to work. As long as the software can read the files and folders customers want it to manage, axle ai will automatically create low-bandwidth proxies accessible via any web browser, regardless of where the files are stored or what operating system is being used.
Next, in late 2018 Axle.ai introduced its connectr.ai visual workflow tool, which enables users to build and deploy automated video processes through a drag-and-drop graphical user interface with minimal coding knowledge. These processes include things like automatically applying common metadata, video encoding, archiving media on storage, and uploading files to a local network or the cloud. Previously, media teams would often need to enlist software engineers to create expensive custom solutions to help them realize the efficiencies of such process automation.
Finally, in November 2019 at the annual Adobe MAX conference, Axle.ai launched its third primary product, ascribe.ai, a speech transcription service plug-in that operates within Adobe Premier Pro. Ascribe.ai was notably built with the same speech technology used by the company’s core axle ai media-management software. In contrast to axle ai and connectr.ai, which are priced on a per-user license model (a two-user license of axle ai 2019 currently costs just under $3,000, for example), ascribe.ai follows a “freemium” pricing approach through which users are given one hour of transcription services for free. After that, they have the option of upgrading to subscription plans ranging from $4.95 per month (for 2.5 hours) to $120 per month (for 80 hours). With even the least expensive option providing transcription services for less than $2 per hour of footage, and with each minute of footage taking as little as 10 seconds to return results to the Premier interface, the Axle.ai team lauds ascribe.ai as offering the “best price-performance of any speech transcription platform available today.”
A High Margin Software Business
Speaking of sales, all three of Axle.ai’s products are already contributing to the top line. The company recorded revenue of $853,807 in fiscal 2019, showing good for year-over-year growth of roughly 7.8% despite introducing ascribe.ai late in the year. At the same time, Axle.ai has yet to achieve sustained profitability, incurring an annual net loss of $248,808 after recording operating expenses of just over $1 million in 2019.
However, the potential for juicier net profits is there. After transitioning away from a mixed software/integration business approach and toward a pure software model last year, Axle.ai’s gross margin improved by a staggering 11 percentage points to 90%.
If Axle.ai can effectively position its software offerings as reasonably priced cutting-edge solutions that cater to the fast-growing number of media teams seeking to make the most of their video libraries, it could scale at a rapid pace for years to come. If it can maintain those healthy gross margins when that happens, the company should be able to enjoy significant operating leverage as its top line grows.
An Enormous, Growing Market
We noted earlier that more than 70% of the $10 billion video-content management market is spent on innovative software solutions for the niche, which itself should serve as a tailwind for unique products like Axle.ai. The company should also benefit from steady declines in the cost of implementing viable video-content hardware storage solutions going forward, particularly as improved affordability of media storage products encourages growth in the number of small and medium-sized media teams.
We also mentioned above that Axle.ai already counts more than 600 such teams — generally from three to 30 people in size — among its paid customer base. But it’s not just smaller clients coming aboard. Axle.ai’s customers include top brands and industry powerhouses like Warner Brothers, Amazon, Facebook, Accenture, Coca-Cola, Patagonia, and PWC.
While you certainly won’t find Axle.ai management complaining about winning the hearts of their largest clients, there’s no denying small- and medium-sized customers represent a massive opportunity: The company believes its current total addressable market (TAM) is closer to 300,000 customers today, and further estimates its TAM could roughly double to 600,000 clients over the next four years.
To that end, Axle.ai claims it’s enjoying “strong interest” from its mailing list of over 40,000 organically generated industry contacts, many of whom are finally realizing the potential benefits of implementing media-management software for the first time.
At the helm of Axle.ai co-founder and CEO Sam Bogoch, who previously worked for five years as Director for Software Development at publicly traded broadcast media solutions company Avid Technology. During his half-decade here, he helped to more than triple Avid’s sales from Interplay and Media Central products to $55 million. This experience also undoubtedly gave Bogoch a unique perspective on the shortcomings and underserved opportunities left vacant by more expensive enterprise-centric solutions from larger companies like Avid.
Fellow co-founder Patrice Gouttebel now serves as Axle.ai’s VP, Product Management — a logical transition given his previous role as product manager at digital asset management company SeeFile. Notably, Axle.ai’s team page claims Gouttebel boasts “extensive experience with web coding, user interface design, and perhaps most importantly, direct customer dialog.” This indicates he might simultaneously prove invaluable in a sales engineer-esque capacity by communicating to inquisitive customers the unique strengths of Axle.ai’s highly technical products.
Meanwhile, VP of Operations Katy Scott is the company’s third co-founder who continues to work in a managerial role, handling resource allocation, support and installation schedules, and company financials. Katy graduated from Fitchburg State University’s Media program and previously worked as a freelance photographer for eight years, bringing a unique perspective of the media industry clients to which Axle.ai caters.
Finally, co-founder and Lead Engineer Steven Ryan previously lended his years of software programming skills as Lead Programmer for digital asset management company SeeFile, developed compilers for enterprise engineering software company Intergraph, and built distributed computing and client-server programs for motion control and automation products specialist Torque Systems.
Between its capable leaders, its enormous total addressable market, and its differentiated high-margin software model, we have determined Axle.ai is a Top Deal for prospective investors to consider.
As with any budding business, that’s not to say there aren’t headwinds facing the company today. Competition remains a key risk, as any number of well-funded peers could move to lower prices and improve broader-market appeal for their respective solutions. However, Axle.ai’s head start as a first mover to fill the gaps left by competitors should serve it well to that end.
Investors should also remain cognizant of the impact of the ongoing coronavirus pandemic, which will almost certainly hurt capital spending across all sectors. But here again, given the cloud-based features and platform-agnostic nature of its solutions, Axle.ai might also be well-positioned to help some clients more easily navigate the challenges brought by COVID-19 by continuing to work remotely with their teams.
All told, we believe Axle.ai’s early momentum is a telling sign of its potential for success going forward, and it deserves a Top Deal designation.
About: Steve symington
Steve Symington is a Lead Advisor at 7investing Group, and previously wrote thousands of articles on publicly traded equities, personal finance, and investing while serving as an analyst for multiple real-money portfolio services at The Motley Fool. He holds a degree in Computer Science (with an emphasis in software systems and mathematics) from the University of Montana, and previously worked as a software engineer implementing machine-learning algorithms primarily for military and government clients.