Autonomy for industrial control systems
Autonomous systems use reinforcement learning and machine teaching to bring autonomy to industrial control systems across multiple industries.
Maximize throughput
Dynamically adapt to multiple and changing optimization goals to maximize the throughput of many processes.
Reduce operation costs
Reduce operation costs by improving process efficiency and reducing machine downtime through autonomous machine calibration and optimization.
Enable new levels of automation
Intelligent control systems can tackle industrial processes that were previously too dynamic and complex to automate.
Manage resources efficiently
Make your people more efficient and your industrial processes more sustainable.

Process optimization
Automatically control dynamic and complex processes for maximum output, minimum downtime, and reduction in part failure.

Machine calibration
Faster machine calibration and tuning exceeding operator-level precision.

Motion control
Optimize movement and trajectory for robotic arms, bulldozer blades, forklifts, underground drilling, rescue vehicles and more.
Energy systems solution accelerators
Energy systems solution accelerators can help you manage building environment and efficiency by using AI to maintain a set temperature, minimizing energy costs, and extending equipment lifetime.
Explore energy solution accelerators

Autonomous Underground Horizontal Drilling
Control drilling path to optimize oil yield while avoiding lease lines and other oil rigs.
Business problem
Maximize rate and volume of oil extraction from subsurface asset via horizontal drilling.
Current limitations
Human operators follow and iteratively adjust the prescribed well plan based on static geophysical models. Inaccuracies in geophysical models require constant adjustments based on imprecise sensor data, reducing percentage of time drill is extracting oil on plan.
Project Bonsai solution
Eclipsed human-like performance within one week. Drill bit never deviated more than 2’ from optimal path. Reduced time to complete drilling operation more than 20%.

Wind Farm Energy Output Optimization
Maximize energy output of wind farm by controlling operating parameters of individual turbines.
Business problem
Maximize energy output of wind farm by controlling operating parameters of individual turbines.
Current limitations
Human operators supported by custom optimization algorithms. Human operators struggle to comprehend voluminous sensor input, and algorithms that model dynamic operating conditions are still emerging.
Project Bonsai solution
Trained BRAIN to match controls benchmarks in 3 hours and extended approach to other five control parameters combining them across the entire wind farm.

Asset Yield Optimization
Maximize yield through standardized approach to optimized control decisions.
Business problem
Inconsistent production yield of land or offshore asset because of complexities in choke valve control tactics.
Current limitations
Production engineers and operators make control decisions several times per day based on pressures and flows. Extensive experience required for veteran production engineers to understand and optimize complex interactions, resulting in dramatic output differences.
Project Bonsai solution
Automated recommendations 24x7 that produce more output than Offshore Control Room Operator recommendations. Automatically operate choke valves for an oil field from control room to maximize oil production.

Control a conference room HVAC system
Simultaneously optimization of temperature comfort, energy consumption and compliant CO2 levels.
Business problem
While conference rooms are unoccupied about half of the time, HVAC systems are predominantly operated by simple PI thermostats, consuming energy when unnecessary, and sometimes violating CO2 safety levels.
Current limitations
PID corrections are reactive, while MPC controllers consider future state but still struggle to find global cost optimization behavior. Both approaches require time consuming commissioning process to tune controller behavior.
Project Bonsai solution
The autonomous system learned to control HVAC for improved comfort and air quality with ~23% lower energy consumption.

Partners in autonomous systems
Our system integration consulting partners can tailor our autonomous systems technology to your specific industry and use case. Leverage our network of experienced partners and simulation solutions to help you build intelligent autonomy into your industrial processes.

Project Bonsai solution accelerators
Solution accelerators provide development resources, integrated simulators, and customizable machine teaching plans to kickstart your industrial AI solutions.

Explore Microsoft AI platform
Microsoft AI is a robust framework for developing AI solutions in conversational AI, machine learning, data sciences, robotics, IoT, and more.

AI Lab
Learn from labs that demonstrate how autonomous solutions can be applied to drone simulations, intelligent robotics, and more.