In this series, we demonstrate how we have applied our solutions to a variety of different projects in over twenty years of business. Last time, we went over solutions in knowledge platforms. Now, here in part 5, the finale, we will show how we have applied solutions in wisdom AI and learning to a variety of projects. Like before, we will list out the solutions themselves and projects that fall under each category. Furthermore, we will also address the challenges involved with these solutions.


Wisdom seeks to provide the answer or recommended options to “What should we do?”

Most human wisdom is not pure classification sorting, algorithmic logic, or programmatic decisions.  Wisdom lives in a world of “chaotic and fluid and yet to be captured in a way to be used yet” data. Wisdom will require creation of prediction/solution set based on copious amounts of collaboration to truly bring the data together. These solutions will require support data to be built on top of the learned and signal data that relies heavily on data science and computer science models. which rely on natural language processing, higher order linked data, fuzzy logic, interpretive signals, artificial intelligence, sentiment analysis, and low-level atomic big data analytics. Without this context, which is both exciting and unsettling in the same moment, wisdom solutions will remain on the horizon in general, and be applicable for niche-specific solutions. While in its early phases the “What should we do about it?” our solutions offer:


  • AI & Machine Learning Platforms – 
  • Massive streaming aggregations
  • Data Science AI Workbench platforms –
  • A/B Signal testing & acceptance/rejection lifecycle
  • Multiple-ontological and linked data solutions
  • Sentiment analysis
  • Low-level atomic big data analytics –

Challenges to Address

  • Create high quality AI/ML training data to address the promise of AI technology solutions – solutions rushed into production will not yield results replacing human interaction.
  • Integrate historical data with near real-time, and real-time data to support more robust and higher fidelity analytics
  • Provide Temporospatial analytics to automatically provide ranging guidance, predictive analysis, or recommendations 
  • Integrate beyond traditional sensor data, foundational data, and thematic data with newer data integration with social, behavioral, incident, or citation/criminal data

Thank You For Joining Us

It’s always fun for us to take a trip down memory lane and think back on everything we’ve done. Call us nostalgic, but when you’re in business for over 20 years, sentimentalism seems to be inevitable. Also, it’s always nice to point to actual examples of the solutions we’re so proud of. Thanks for sticking with us through this five-part series.