Years ago, prior to Y2K, I had a meeting with an acquaintance who was a small-time broker in Northern California. He had built a “system” designed to watch fluctuations in stock price. His theory was that if you bet on a small upwards curve followed by a small dip it would naturally go up – like an sine wave of increasing amplitude. Even at the time, I knew his system was nothing more than guesswork, and when Y2K hit a few years later, it hit that broker and his clients extremely hard. Lesson learned.

Even though my broker acquaintance was betting on pure speculation, I sensed that the major reason he was wrong wasn’t that there aren’t discernible patterns, but that he wasn’t actually looking at the data or patterns that mattered. Looking at a graph is good for many things, but using them without context is prone to failure. What if I could provide a lot more context? Or even better, what if I could forgo the boring analysis part on behalf of clients and only deliver context?

For almost two decades, I pondered how I could build something like this, using a unique skill set that I had amassed from a career in computer security, and Internet-scale data. It wasn’t until 2013 that the technology to perform advanced internet analysis became readily available, drive speeds had increased to the point that they were useful for real-time analysis and costs of drive density fell far enough to make this dream a reality. So drawing on decades of Internet, security and business experience, I finally began developing the corporate intelligence tool I had been dreaming about for my entire adult life.

Early on, as I was developing a prototype, I wondered what this company would be – is this company a hedge fund, is it a research tool where clients perform their own research, or is it something else? In a bit of a Field of Dreams moment, I had to wonder if I was building something that anyone would even use. Sure, I knew it was useful, but maybe no one would understand my vision. When I talked to VCs, they said I was on to something and that I should sell my company to a hedge fund – but the multiples were low on a deal like that and the VCs wouldn’t invest (not that I needed the money anyway). The idea was good, just not something they’d invest in, which was great validation but hardly cause for a ticker-tape parade!

When I talked with hedge funds they all agreed that the data was incredible, and many said that I should start my own hedge fund; but having never done it before, that was daunting concept. Alternatively, others said that the data was incredibly useful and that I shouldn’t give it to anyone, lest it become less valuable over time. I saw right away that they were telling me that they wanted the data for themselves. That gave me a total addressable market of one hedge fund – a non-starter. Don’t get me wrong, I would have sold for the right price, but I don’t think we were even in the same ball-park, to continue my Field of Dreams analogy.

Then I talked to several accredited individual investors who also agreed the data was amazing, but the analysis part was daunting for an individual investor who lacked the experience that I had. They recognized that it was useful, but even the more savvy technically competent investors who were shown my prototype analysis engine interface told me, “No one should ever see this interface, it’s just too complex.” Meanwhile, they spent the rest of the meeting looking through the data, doing the same analysis that I would do. So if the data is useful, and people want it, but they can’t understand it, where does that leave my budding prototype, I wondered.

I was left with the next logical choice – build a service that does the hard work for my clients. That is how OutsideIntel was first born. Finding insider quality information from the outside – legally. I was naturally concerned about the legality, but as I probed, I found more and more mounting evidence that what I was doing was simply great research.

At one point I even had an agent of a three letter agency look at my tool and he remarked that it was amazing, asked me to look up some companies for him that were “of interest” and asked me to please make sure that I never gave any of the raw “.gov” or “.mil” information out to any unscrupulous parties – he feared that the data was so good that it verged on national secrecy issues. But the good news is that it’s legal, and for corporate intelligence, hugely useful in lots of cases.

When I had had a chance to improve my prototype after shopping it around, even my Wife remarked how unbelievably scary the data was when I ran it against some companies and found their client list, how they were evolving, which areas they were growing in, and so on. It’s always a good pressure test to get the thumbs up from the Wife. And the best part is that I was just getting started.

However, one thing I worried about a great deal was explaining to people the types of sites that were most well suited to this type of intelligence.  I felt a great deal of anxiety about having customers ask me for information on companies that are primarily brick and mortar or stagnant.  Even if my technology is sound, the last thing I want to do is let people down and field angry feedback.  So I decided to change the whole concept to being a simple, but powerful blog to demonstrate stock and corporate intelligence using a platform of my own design.

This blog will be a place to highlight just what this intelligent system is capable of providing.  Eventually, I aim to sell the technology and data to an interested party, but for now, anyone who finds this information of value can get previews into the technology.  Down the road, should a financial investor, hedge fund or private investor purchase this technology, I cannot guarantee what this blog will become.  But for now, I hope you enjoy OutsideIntel – the corporate stock intelligence platform!


Robert Hansen – OutsideIntel corporate and stock intelligence platform author

-Robert Hansen