What is IntrospectData?

We're a company focused on leveraging modern techniques in data analysis and reporting to drive a new breed of business intelligence tooling - one focused on answers instead of overwhelming decision makers with more and more data to interpret.

We started with solving our own problems...

After being subjected to thousands upon thousands of reports, data summaries and dashboards, we realized things were getting a little out of hand and we'd lost focus on what really matters in actually using all that data we all collect - that it's only useful if you're using it to drive decisions. The day we saw an 18 page 'report' based off of data that would have only spanned 13 of those pages we knew something was broken, so we set out in search of a solution to the problem.

...Then we did our homework...

Starting with some basic statistics background and a deep frustration with the amount of useful insights we were potentially missing out on in our own lives, we hit the books and worked our way from the foundations of Information Theory through to modern day data science practices and were amazed at what we found. Not only did we learn a lot but we saw a clear set of problems emerge and we discovered we were on to something with our frustrations...

  • Even with well designed reports, lots of decisions are still made by 'gut feel.'
  • Confirmation bias runs rampant in the process of developing and interpreting reports as well.
  • The amount of data being captured is skyrocketing and current techniques to make sense of it just aren't adequate.

...And WE Decided we could do something about that.

We've been writing software for decades, have consulted to and for some of the largest and highest scale organizations in the world and helped them build stronger engineering and product culture while driving technical excellence 'in the cloud.' While we've written applications and services in nearly 'every language under the sun,' coincidentally, Python, R, Golang and a few others that we spend more time working in continued to come up in our research and that sparked something in us:

What if we took our high-scale application design, development and management skills and turned it on this problem of creating a platform to help drive decisions instead of just more reports?

Our old mantra of 'build faster' that drove us to automate even the generation of our code in some areas had us asking a more general question - can we help businesses make better decisions, faster and with more confidence? In today's age of machine learning, artificial intelligence and the ubiquitous 'cloud,' our answer to that question was a resounding 'yes' and we started building.

Our core values.

These values aren't just another attempt at marketing, we hope to show not just that we're 'focused on the customer' but HOW we go beyond customer service to truly understand and solve your problems today, tomorrow and over the long term. What's more important to us is how we build our team and a culture that enables a depth of focus on data problems that spans multiple disciplines, personas and even multiple market verticals. With that, we try to keep it simple and we focus on four things we believe are critical:


We wouldn't have started thinking about the idea of IntrospectData if it weren't for our own curiosity. With that, we see curious interest, questions and even half-baked ideas as  a stepping stone to how we can build better product, better teams and ultimately a better company. We don't just have a 'suggestion box' - we openly encourage it in our daily work.


If curiosity is important, being able to satisfy that curiosity is critical. More important though is being able to do so in a way that's 'safe' for our customers and the data they entrust us with. We see this as one of the critical reasons that automation permeates our processes from end-to-end. When it's safe to 'play,'  it allows us to iterate more quickly and leads to a more stable, consistent and scalable product.


When we're working on new product, with our clients or even internally on 'all that stuff that runs the business,' we keep the focus on what the end result looks like. We're intentional in our approach, our design and in how we interact with others and are constantly leveraging this focus to be more creative and efficient about 'how we get there.'


Whether we're talking about Claude Shannon's defintion or the surprise of an impromptu party at the office, good or bad, surprises are inputs and we're always looking to take surprises and drive value out of them. Unexpected relationships in data drive us to ask 'why' and 'what can we do with that?' Parties at the office just have us asking 'when's the next one?'