The need to inventory milkweeds to add 1.8 Billion new milkweeds across North America was the catalyst for building POLLi.

SBA optimized a data collection process with drones. The result is a process that saves time and cost with better accuracy. We designed our solution to facilitate machine-learning observations of different plant and animal species.

The flight planning tool supports off-the-shelf drone technology for private land operations and drones on the Blue sUAS list, enabling deployment on federally owned lands. Then, we automated the data analytics pipeline to evaluate 100 images per second and count all milkweed in each image – Crazy fast!

Combining machine learning, computer vision, GIS information, and other data layers, SBA has created a tool that will work with machine learning results for multiple plant and animal species and support numerous use cases.

The entire solution consists of a flight application to capture data with a drone, a platform to manage ML/CV results, and a mobile application capable of supporting manual observations stored in a database. Accepting new machine learning and computer vision algorithms and data products is expandable.

Our customers find value in what we do by reducing the time and cost of creating object detection tools and performing object detection tasks.

AI for complex tasks holds significant promise in performing processes that need human intelligence. The organizations that adopt AI will propel ahead of their peers that don’t. They will become more efficient, improve customer experiences, and make better business models producing better decisions and leading to better outcomes. Adopting AI can solve complex tasks in a scalable way and far surpass the performance of current practices.

SBA is working with its customers and partners in developing AI specific to their objectives. An example of AI our customers employ is machine learning applications used in conservation, land management practices, and mining.

When we started developing PitPartner, SBA worked with industry partners getting dirt under our fingernails to build a solution that provides economic value for our customers. We aimed to create a workflow and value akin to hiring an extra employee at no additional cost, and we did.

PitPartner is a beautiful example of how we developed a tool to save aggregate pit operations money and time while helping them capture more revenue from work they’ve already done.

PitPartner is a cloud-based solution connecting the loaders, trucks, customers, haulers, and materials data through an application that operates across all devices, improving communication and time savings across an entire pit operation. Most accounting tools quickly consume the data to improve efficiency and accuracy.

Today, PitPartner is one of our Earth-Changing Solutions.

Our customers include electrical power generation & distribution, transportation, aggregate mining, wind & solar energy production, NGOs, carbon sequestration schemes, and land management practices.

We design and build software, automate machine learning processes, leverage the power of GIS technologies, and create computer vision analysis solutions capable of aggregating observations for decision-making at scale.

Our solutions fulfill unique voids in critical land-use practices like right-of-ways that often perform an essential role as bio-diverse habitats for multiple species.

Changing land use practices, environmental pressures, and conservation incentives create unique partnerships to improve biodiversity.

We’re building the tools to assist these disparate partners in ways to work toward a common goal and communicate on a common platform.

SBA has created state-of-the-art technologies to evaluate imagery captured with cameras, satellites, and multispectral sensors to answer big questions about bio-diversity and land-use practices.

We have also created ways to assist you, the SME, by enabling direct participation in the machine-learning and data-training process. You will use our MLOps framework and best practices to assist in training the algorithms and achieve the best result faster and less expensively. If you prefer a full-service option, we do that too!

We’ve only begun to scratch the surface of what is possible. Adding context by asking the same data different questions or complementing current data with other machine learning results provides greater insight. We’re working with customers to do just that.

The complexities of nature require many observations for a limitless list of needs. We can’t do it all and want others to join us in the effort.

To do that, we have created a tool to support an assortment of conservation models that will assist in collecting and managing object identification results to reside and function on the same platform.

Disparate conservation solutions are one-offs and lack the insight multiple observations provide biodiversity, and we are improving how data collection and analysis can be accomplished.

Now, algorithm developers and technology producers can complement other data and information. SBA can help you focus on your core competencies with a tool to capture, visualize, store, and evaluate the data and machine-learning results you’ve created.

Our platform can help build context outside your core objectives by visualizing observations, sharing the data with others, or combining other data layers to achieve more significant insights.

To simplify the process, we have APIs to seamlessly automate the inclusion of your analytics results into POLLi.

If you are working on conservation applications, SBA’s POLLi platform is the final tool for your solution and a conduit for monetizing your technology quickly.