Source AI and Why You Shouldn’t Buy Custom Furniture
At BCG, what we have to deliver as a consulting company has changed in recent years — a lot. We are no longer responsible for delivering strategies; instead, we’re tasked with delivering solutions. But while in one industry or domain such a change is usually fairly simple, imagine working for a company where those solutions have to address every problem space in every industry. Yeah, I’ll just let you ponder that one for a second.
What that means is that we have to define and understand the art of the possible, because at BCG, our job is to make companies as close to future-proof as possible. How do we do that if we don’t have our hands on the pulse of the world’s most cutting-edge innovations? We need to be ahead of the game not only in strategy but in artificial intelligence (AI), machine learning, high-performance computing, computer vision, AR/VR…the list goes on.
We need to prove that not only can we come up with good ideas, but that we can engineer and build high-quality products around those ideas, at accelerated speeds. And with a dash of eye candy thrown in for good measure.
In light of those foundational goals, we decided to solve one of the more complex challenges we believe exists today: successfully deploying full-scale analytics applications in production environments and across core business systems, at blazing speed. Our eyes crossed a bit just thinking about it, but we hit the whiteboard. And 11 months later — yes, you read that right, just 11 months — in November 2018, Source AI 1.0 was born. And we think it’s one of the best products the market will see over the next two to three years.
Don’t be a Susie
In order to make clear what Source AI is and why it’s so powerful, let’s use a very simple analogy: furniture. I think we all have furniture but if not…well, I’ll leave that for another blog post.
Susie’s custom furniture story:
Susie gets a new job and soon afterwards, buys custom furniture for her 400-square-foot NYC apartment. It fits into the space amazingly well, looks great, and is super custom, so no one else has it. A special company had to come in and put it together for her for an additional cost, but it’s totally worth it. She’ll be the talk of the town!
Susie soon realizes that she also needs more basic furniture, too, so she buys some of that. It’s not as expensive as her custom furniture and she saves some money by putting it together herself.
Two years later, her company relocates her to the Midwest, where she gets to live in a 1000-square-foot apartment. Woohoo! More space! But wait — her custom furniture fits, but because the apartment is so much bigger, the spacing is off. So, she buys more custom furniture and either throws out the old stuff or puts it on Craigslist. And she hires more new people to put her new custom furniture together because, why not? Her bigger place is awesome!
She’s all set. Her place looks great, and her interior design reputation is intact.
Another two years goes by and she gets a promotion, so she needs to move…back to NYC. With her promotion she’s making more money, but it’s NYC, which means she can afford just 600 square feet. And, well, we all know what happens next…it’s furniture revamp time.
The morale of the story, dear reader, is that you never know where you’ll be in five years. So, quit buying the custom furniture and hiring the custom carpenters, because you’ll waste a ton of money, have no bed or couch to sleep on, and end up sitting in your new apartment on the floor eating NYC Chinese takeout (very good Chinese takeout — it is NYC after, all — but still).
Now let’s imagine you’re the CTO of an organization that needs to future-proof itself. You have two options:
1. Do what Susie did with her apartments: keep buying a ton of new stuff, hiring different people, and re-working the cycle every time your situation changes, even slightly. Why not? It’s worth it, and you have the budget for it, right?
or
2. Adopt a few modular tools that will evolve with your organization and people regardless of where the world takes you both.
The second option is why we built Source AI; it is modular analytics development and deployment software that will evolve with your organization.
What Source AI is
Source AI is more than just your typical analytics software. Much more. Source AI is:
Complete yet configurable — We broke down tool silos to ensure that data engineers, data scientists, analysts, and executives could all use Source AI in different ways.
Modular and industry-spanning — It uses open source tools so that it will evolve along with those tools. And it has an open application layer that lets you build the applications you need for the use case you need, when you need it.
Fast — Source AI can deploy applications from the point the data gets ingested to the point the analyst sees it on their iPad in under a day. Sort of like having the new place you moved into that day fully furnished by the time you’re ready for bed.
Cutting-edge — With a patent pending, GPU capabilities, and several awards under its belt in the less than three months since it was released, Source AI taps into the art of the possible alongside the core problems it needs to solve for.
Special — We put a bit of our own secret sauce in to make sure all these tools can work together securely, resiliently, and effortlessly. Think of it as the Gorilla Glue that holds all that modular furniture together.
Source AI is, in other words, the solution you need when you simply don’t know where the world will take you.
Source AI in practice
But let’s dive even deeper. Here are how five key people in any organization can use Source AI to make the work that they do be more efficient and impactful while taking significantly less time to complete. We’ll start at the top:
The CEO — Your organization is about to embark on a digital transformation to reduce costs, drive innovation, and create new revenue streams. But your board isn’t quite sure what this means tactically and so has a number of questions and concerns they want answered before they’ll believe this transformation is worth the investment.
The CEO with Source AI — While technically you’ve got a cart-before-the-horse problem, with Source AI you can get started building analytics applications on our cloud or in your private enterprise in minutes. Which means you can have a sleek application that will enable you to illustrate to your board what their next-generation organization will look like, all by the time the directors next meet. Source AI helps you win early.
The CIO/CTO — You just heard from your CEO that you will need to modernize everything in the organization, and fast. You will need to figure out what technology to build and buy, what data to gather, who to hire, who to outsource to, and how to manage a seemingly small budget.
The CIO/CTO with Source AI — You can leverage the build-operate-transfer model of Source AI to kickstart your technology transformation. Using our software will buy you some time so you can build the foundational elements of your new tech architecture while the business is gathering information that will help fund your next-generation tech strategy. Not only can you buy some time with Source AI, you can see how we built it, understand the open source components, learn from our engineers, see how we manage costs by staying modular, and then apply those modularity, open source, and microservices lessons to your own budget.
The Quant (analyst/data scientists) — You need to provide fast results but you are constrained by your analytics environment.
The Quant with Source AI — Source AI pays special attention to quants. It’s not a new software technology that takes months to learn; it’s comprised of what you already know: command lines, Jupyter Notebooks, IDEs, hundreds of analytics packages, and a feeling of working off of your own laptop. And it grows with you and your organization. You can bring both new and any traditional models you’re comfortable with into Source AI and it will make sure your infrastructure, code bases, and products are managed and developed to production standards.
The Engineer — You need to keep the lights on, make sure all the work the quants are doing is industrial-grade, and keep the company machines humming. In the meantime, you’d love the chance to tinker with new ideas and products that could help you in your job.
The Engineer with Source AI — Source AI removes all the hassle of DevOps. It helps engineers easily develop applications and expands its capabilities to meet their organization’s unique needs — including connecting with what the quants are doing, which accelerates everyone’s processes. You can use Source AI to build a new retail application, for example, or a new piece of data functionality to ingest public data sources for your analysts. And by easing the pain of setting up, testing, checking, productionizing, and securing data and code, Source AI is also a playground for engineers.
Business lead — You want answers, you want them fast, and you want them to be easily accessible — in one place that is easy to find — so that you can make better decisions for the organization.
Business lead with Source AI — Because you can easily build custom analytics applications on top of Source AI and because Source AI is also being used by the quants and engineers, with it you can take a business application from napkin form to reality in as little as one week. You may even be able to find unrealized revenue faster and react to market trends and economic shifts more quickly, also known as being “agile.”
As the examples above make clear, Source AI is not just a software tool; it is a catalyst for collaboration, innovation, and decision making. It is a force multiplier for analysts, data scientists, and engineers. It is designed not to lock your organization in, but to free it up so that you can take your capabilities to the next level.
More to come
While our competitors may claim to do the same thing that Source AI does, we hold patents, and our dream team — which can be found on our website, source.ai — includes people that once worked for Amazon, Facebook, and on Anaconda Python, among other cutting-edge environments. This gives us a very special view into the world of analytics, technology, digital disruption, and growth.
Our team’s next blog post will dive into the nitty-gritty of how we built Source AI and our unique uses and applications of Go, Kubernetes, graphQL, Docker, Docker Trusted Registry, Terraform, Vault, CUDA, and more.
In the meantime, we welcome you to start learning more about how BCG GAMMA and GAMMA Engineering are making strides in AI, engineering, distributed processing, visualization, and other fun topics. As you’ll see, we keep our bar high.
