Geolumina
Houston, Texas, United States
Geolumina
!
Creating AI to enhance subsurface workflows.
About Geolumina
A little history
In 2018 Kali developed machine learning code to identify birds. David saw this and thought:
What if we apply this to the subsurface?
At the same time, David and Stephen were tossing around ideas for creating a business based on their deep combined experience in the subsurface.
Thus Geolumina was born from birds.
Our founding team is uniquely positioned for success. We have deep experience in scientific, computing and business disciplines essential in this space.
David ran the world’s largest upstream petroleum systems research group and is a patent holder in geoscience technology
- Kali is a programmer with over thirteen years of scientific computing experience across a variety of disciplines
- Stephen is a seasoned geoscientist, having been on the ground in 70+ countries working from the well site to the board room
- Combined, Stephen and David deployed over $600 million in private capital
We met ten years ago and experienced immediate chemistry which grew to shape our vision for this company.
Description of Services
- Expert knowledge unleashed by AI
Work smarter, not harder
Geolumina's NVZN AI system is an end-to-end product for capturing and scaling insight from images.
- We have a killer set of tools
Real world data is messy. Geolumina's NVZN system cleans it up by:
- Locating image files
- Extracting images from documents, including powerpoint and PDFs
- Organizing images using computer vision and natural language processing
This is foundation for protecting, unlocking, and scaling insight from your images.
- Simply Powerful
The subsurface is complex, your workflows don’t have to be.
Once data has been ingested with NVZN, the sky's the limit for analysis and model creation.
Apply our built-in models to or scale your own expert insights with 80% less effort than existing products.
- Limitless possibility
The most common question we get is 'can you do this with my specific use case'. The answer is YES! The NVZN system works on any image type. Here are just a few use cases.
