We have decades of experience building complex systems and navigating many rounds of technology revolutions. And the result is a growing collection of applications that use the latest in AI technology married with enterprise features.
We’ve experienced difficult lessons and impactful innovations. And we want to share them with you.
Every platform revolution—the Personal Computer, the Internet and the Mobile phone—ushered in a wave of disruptive business applications. We know, we were there at some of the most influential companies making it happen. Each built from the ground up, natively tailored to each platform, each did so much more than introduce new features; they abstracted complexity and accelerated productivity in ways only imagined and fundamentally redefined how work got done.
The Personal Computer brought us Lotus 1-2-3 and WordPerfect. Before these apps, complex calculations and document creation were painstakingly manual, consuming hours or even days for what we could consider the most basic of tasks today. Windows introduced Microsoft Office and Outlook, merging essential apps like word processing, spreadsheets, and email into a unified suite, where before users juggled disconnected apps from different vendors, creating fragmented workflows data silos, and incompatible file types.
The Internet and the Cloud brought us Salesforce and Google Workspace, integrating real-time collaboration, sales, and customer management into the core of business operations. Previously, working on files as a group was clumsy and universal access to content was limited.
The Mobile Revolution introduced the idea that you could have a computer and access to the entire Internet in your pocket. For businesses, it meant a new way to reach out to customers and great efficiency. Today it’s hard to imagine a world where information is at your fingertips and you do everything from buy a train ticket with it to purchasing a car online.
Sure, it’s easy to use the most successful applications in history as examples. But it’s intentional. These apps were not just about technology, they created new paradigms of working. They were more than tools. They abstracted old complexities with entirely new ways of thinking about how to solve complex problems. They changed the world.
Now, while it may sound a bit corny, these apps share what we call a “DNA of Disruption.” And in doing so, at each platform evolution, they reset the user expectations and introduced new business models.
They Exploited the new Platform. These solutions were built specifically for each platform (DOS, Windows, Internet) and fully leveraged new capabilities without legacy constraints, allowing rapid innovation and cost-effective operation by avoiding outdated system dependencies.
They Abstracted Complexity. These apps turned fragmented workflows into cohesive, user-friendly suites or workflows, enabling users to accomplish more with minimal training, which sped up adoption and reduced training costs.
They Were Designed for Everyone. Intuitive and accessible, these apps empowered users across all technical levels, leading to widespread adoption, minimizing workflow disruptions, and enhancing productivity across varied skill levels and company sizes.
They Had Disruptive Financial Models. With innovative pricing, flexible packaging, and scalable distribution, these apps lowered entry costs, drove enterprise-wide adoption through new go to market strategies.
And while this may seem overly simplified, this is NOT the case with many companies nor many applications.
We are now at the beginning of the AI platform revolution.
But where are the disruptive business applications?
Well, despite the significant advances in LLMs and massive investments in AI infrastructure, we’re still waiting for the disruptive business applications that helped define past platform shifts, to materialize in the world of AI.
Today’s AI tools function largely as chatbots or copilots, sitting alongside existing applications but not fully transforming workflows or unlocking AI’s potential for deep, actionable insights and recommendations across systems. Sure, they add a layer of intelligence, but they stop short of delivering the game-changing productivity gains we know AI can offer. And while the potential for AI to streamline this complexity and synthesize vast amounts of data is enormous—it remains locked behind a technical barrier that few can cross. Data is often siloed, formats vary, and workflows require intricate configurations or custom scripting that demand a level of technical skill and time commitment beyond most users.
Enter Total Neural Enterprise (TNE.ai for short) with three critical lessons that will bring you success in the AI environment.
Unit Quality Matters More than Numbers. In normal times, having a big megaphone, or thousands of people or billions of dollars counts. The big guys can throw their weight around, they are the safe and sensible choice even if prices are high, there’s less risk. But in times of revolution and disruption, the tables are turned. Individuals with insight and vision and great skills can build better products and move the industry forward much faster. The trick is find those teams that have those qualities.
Earning Your Trust and Being Committed. Every revolution involves risk and we’ve learned over and over that “under promising and over delivering are the key to success.
Time Tested Process of Start Small and Delivering Immediate Value. Yes, you can have a big vision, but what counts is delivering immediate results and “delight” to users. The PC was a mighty tool, but the simple act of recalculating a spreadsheet and printing a beautiful chart was all that was needed at the start. The same with mobile phones. Just getting bank balance without having to call someone was enough to start the enterprise application revolution in mobile. So finding that small thing that matters is the key
Right for Today and Ready for Tomorrow. At the start of a revolution, there are so many blind alleys and box canyons. There is a temptation to bet early on something from a trusted vendor. But, in times like this, working with groups that have the wisdom to see what’s best for you in the long term is what counts. The trick is to bet on the right long term vision and stick with frameworks and tools that are along that path. It takes an incredible blend of business and technology savvy to do this.
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