at a Glance

Machine Learning & AI for complex multi-spectral & multi-dimensional data
We collect process, analyze and visualize data from multiple sources
Our custom developed approaches bring quality and consistency to your analysis

Our Platforms &

& Expertise

Complex Multi-
Spectral and Multi-
Dimensional Data
  • HD Imagery
  • 3D Models
  • Orthomosaics
  • IR Thermal Imagery
  • LiDAR Models
Data Sources
  • Satellite
  • Aircraft
  • Helicopter
  • Drone
  • Vehicle
  • Hand Held

Each data collection method has strengths and weaknesses. InfraSix team of engineers has done the research to be able to provide recommendations based on your particular needs and data usage.  

Clients are encouraged to collect their own data or InfraSix can arrange for data collection through one of our networks of pilots.  We do everything we can to keep the process efficient for our clients.

Our custom machine learning and data analytics are used primarily to process huge amounts of data in order to pull out the characteristics relevant to each particular client—image-based and text-based.

We are amazed at the amount of work in the area of image analysis being completed manually. Our automated approaches bring quality, consistency, efficiency and professionalism to the analysis and reporting process.

When to Utilize

Too Much Data
When you have more data than you can process and analyze, machine learning presents the perfect opportunity to streamline your process. Don’t let data “fall on the floor” because you don’t have time to process it all. With ML applications, we can process huge amounts of data, even petabytes, efficiently and help you draw conclusions.
Repetitive and Manual Processes
When you are faced with repetitive processes, consider machine learning to replace the manual process. Repetition leads to loss of focus and inconsistency. ML can bring structure to repetitive processes and even prioritize the elements that need further human intervention.
Consistency and Quality Needed
When work is mundane, focus tends to drift. When different staff evaluate data, their conclusions can vary. When you need to have consistent evaluation of data, ML can be very effective. With consistency comes quality because we can develop a baseline and then institute continuous improvement. And when human intervention is needed, ML can highlight the need for additional investigation.
Otherwise Unavailable
Sometimes the only way to process complex data is to utilize ML. We can take extremely complex data into a ML structure and bring out the significant elements that allow for better decisions. When the data becomes overwhelming, ML can be a perfect solution.