Reinforcement Learning Development

The World’s First and Finest Reinforcement Learning Engineers

Not sure? Scroll down...

Dedicated Reinforcement Learning Engineers

Winder’s engineers are world leading experts in reinforcement learning. We wrote the book on reinforcement learning!

Our focus and specialism on reinforcement learning development has allowed us to deliver RL projects to some of the worlds largest and leading AI companies. They leverage our reinforcement learning services to design, prove, and deploy production reinforcement learning products.

Reinforcement Learning Development Services

Winder.AI helps companies build production-quality reinforcement learning products and platforms.

Our book on industrial deep reinforcement learning that we use as part of our development.

World Leading RL Company

Winder.AI are industrially renowned experts in reinforcement learning (RL) and we can help you with your RL problem.

Companies like Nestle work with us to provide expertise where they need it most. Our consulting guidance helps you complete your project faster and to a higher quality that it would have been otherwise. Our flexibility allows us to integrate tightly with your ways of working.

Talk to Sales

Our Approach to Reinforcement Learning Development

Successful projects arises from decades of experience. Take a look at our tips for a successful reinforcement learning project.

Reinforcement Learning Development Process

1. Problem Definition

A key phase where business problems are defined and prioritized. It is worth spending time to get this right, as subsequent effort could be ineffective and wasted.

2. Domain Knowledge Transfer and Infrastructure Setup

Businesses are often experts in their own domain. This domain expertise is valuable to help direct future solutions. In this phase we also ensure any prerequisites are available, including working with our very own ML engineers and MLOps consultants to ensure the infrastructure meets our needs.

3. MDP Refinement

The definition of the MDP is crucial in RL projects. We often iterate over the MDP design to help improve performance.

4. Environment Development/Refinement

The environment, whether in simulation or in real life, needs refinement. Accurate simulations help improve the sim2real problem and updating environments to incorporate new information can significantly boost performance.

5. RL Data Analysis/Refinement

Like much of data science, understanding and appreciating the data is important. Refining what the agent can “see” significantly improves learning performance.

6. RL Algorithm Development

Working on the actual RL algorithm takes a surprisingly small amount of development time, but it is often necessary, especially when improving policy models.

7. Agent Evaluation and Analysis

Thorough and robust evaluation practices are vital for directing development. These results are often shared with stakeholders as a representation of progress. Note how we often iterate back to the MDP refinement to apply new learnings.

8. Deployment and Monitoring

In the final phase we deploy and operate our agents. Do not underestimate this phase; there are a lot of pitfalls, especially when operating at scale. We collaborate with our very own expert team of MLOps consultants to help here.

The OODA loop for continuous innovation.
Winder.AI’s data science consulting strives for continuous innovation. Courtesy of our Reinforcement Learning book.

Continuous Innovation

The infamous OODA loop, originally developed by the US military, is of particular use during our work because it helps promote innovation.

At every phase we look for opportunities to add value and make your products and services better. Our clients find that our work greatly exceeds their expectations due to the extra value presented by our solutions.

The World's Best AI Companies

From startups to the world’s largest enterprises, companies trust Winder.AI.

Selected Case Studies

Some of our most recent work. You can find more in our portfolio.

Announcing Stable Audio: A Generative AI Music Service

We’re pleased to announce the release of Stable Audio, a new generative AI music service. Stable Audio is a collaboration between Stability.AI and Winder.AI that leverages state-of-the-art audio diffusion models to generate high-quality music from a text prompt.

Explain, Enhance and Enrich Your Data with Bacalhau Amplify

Bacalhau is a project started under Protocol Labs, but has now spun out into Expanso, Inc. Expanso is a leading Web3 innovator specializing in developing next generation decentralized commodity services. This case study, which includes a video presentation, describes the proceeds of this collaboration. The Bacalhau team asked Winder.AI to help them develop a new AI product designed to perform data engineering at web-scale, backed by Web3 technologies.

Presentation: MLOps and the Online Safety Bill

This is a video of a presentation about the UK’s online safety bill. This places new burdens on social media companies to moderate content to keep the public safe. This video discusses how platforms are using MLOps to help operate AI solutions that allow them to scale and prevent hundreds of violating posts from being published every second.

Start Your RL Development Project Now

The team at Winder.AI are ready to collaborate with you on your rl development project. We will design and execute a solution specific to your needs, so you can focus on your own goals. Fill out the form below to get started, or contact us in another way.