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Benefits of Our Machine Learning Development

80% of machine learning projects fail. We build the 20%.

Machine Learning Development Introduction

As you know, Machine learning helps your organization automate decisions using algorithms that learn from your data.

However, delivering on that expectation is a lot more difficult than it first appears. The main reason is that building a model that is robust, production-ready, and operationally sound involves a lot of engineering. And a typical data scientist probably doesn’t have the right experience to do that.

Thankfully, Winder.AI have been developing commercial machine learning solutions since 2013 and since then we’ve worked with some of the worlds largest AI companies. All you need to do is talk to us and you’ll quickly realise we’re the real deal.

Take a look at some of the benefits of our machine learning development services below.

Machine Learning Experts

Machine Learning Experts

Looking for experts?

Machine learning experts are hard to find. This is mainly due to the fact that the fields of engineering and data science are broad, complex and rapidly changing.

We’re about as experienced as you can get. And because we’re independent, we’ve worked with a multitude of companies over the years, which multiplies the experience that we can transfer over to you.

Production-Ready Solutions

Production-Ready Solutions

Burnt by data scientists that are good at math, bad at products?

We agree. In fact, this exact issue years ago was what spurred Phil to start training software engineers to become data scientists. He spent several years travelling the world delivering workshops at conferences and teaching privately. Since then many better trainers have come and gone but we still hold engineering ideal close to our heart.

Together with our MLOps services, we provide production ready, operational ML solutions.

Flexibility

Flexibility

Tired of people giving you terms and conditions?

We exist to help companies like yours expand and improve upon their machine learning. Our size enables us to provide exemplary service whilst adapting to your ways of working.

Dedicated To Machine Learning

Dedicated To Machine Learning

Confused by the IT shops that claim to do ML?

Winder.AI is a dedicated machine learning consultancy. We’re not a generic software engineering shop knee-jerking into a new market. Since 2013 we’ve been offering our consulting services and we focus solely on machine learning.

Yes, our offering has expanded over the years as we’ve pioneered new fields like reinforcement learning and MLOps, but we’re still engineering-focused data scientists at heart and we’re still excited by the potential of data.

Machine Learning Development Services

Our services help you extract maximal value from your data

Machine Learning Development Company

By choosing Winder.AI as your trusted machine learning partner, you can be sure that you are leveraging one of the most highly experienced agencies in the world. Our vast experience helps businesses like yous discover value from their data.

Our machine learning developers deliver incredible value by evaluating and recommending strategic business decisions to further your organizational ambitions.

Modelling

Modelling

Let’s get the big one out of the way. Every ML job involves modelling. We take the stress out of your ML development by:

  • Analyzing model complexity and matching it to the data, domain, and non-functional production requirements
  • Thorough, repeatable, hyper-parameter and ablation studies
  • Gitops-powered, empirically-steered development, with full experiment tracking and version control
  • ROI-driven research and development, ensuring we deliver 80% of the value in 20% of the effort.
Data Analysis and Improvement

Data Analysis and Improvement

Improving your data is one of the most underrated aspects of improving machine learning performance. We will:

  • Improve your data quality processes to ensure your models are not being poisoned by bad data
  • Suggest and develop new data sources and new derived data to improve model performance
  • Analyse and remove unnecessary features that add complexity without adding value
  • Utilize state of the art dimensionality reduction techniques to simplify models and make them more robust
Model Deployment and Monitoring

Model Deployment and Monitoring

Leveraging our MLOps services, we will:

  • Ensure trained models are consumable by your services or users by deploying into your environments
  • Monitor your models to ensure they are operational, unbiased, not drifting, explainable, etc.
  • Provide continuous learning processes to retrain models when necessary
  • Track and push important metrics back to your business intelligence systems to quantify ROI and value
Supporting Services

Supporting Services

Don’t for get that we have a range of other related data services that accompany the work that we do. From data science consulting to MLOps implementation, we have the capability to make your AI run like clockwork.

About Us

Winder.AI is a machine learning development firm, and is based in the UK, although we operate globally. Our machine learning developers deliver incredible value by evaluating and recommending strategic business decisions to further your organizational ambitions.

Collaborative machine learning team

Machine Learning Expertise

We're open, unbiased, and flexible enough to work with your stack.

Multi-Cloud

Language Agnostic

Any Library

We ♡ GitOps

Our Approach to Machine Learning Development

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

Machine 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. Exploratory Data Analysis

Honestly, a lot of value comes from a thorough, principled analysis of the data. If you understand the data and the domain, then modelling is a lot easier.

4. Data Processing / Feature Generation

Production pipelines need to ensure that the data is present and correct, and represented in the right way to be effective. This phase feeds into the modelling phase, so good, representative features here make the modelling much easier.

5. Modelling

Finally we’re at a point where we can start to solve the problem with a model. We exhaustively attempt to understand which models are the most appropriate and why. Explainable AI is a key feature.

6. Experimentation

Depending on the goals and the complexity of the model, we sometimes need to develop robust ways of scaling out training. This is necessary to establish which model/hyperparameters/settings/code/etc. is the right choice.

7. Evaluation

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 modelling and EDA phases to apply new learnings.

8. Deployment and Monitoring

In the final phase we deploy and operate our models. 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.

Optimizing for Value Generation

Businesses have three core operational functions. Processes define how businesses run. Decisions decide when businesses are run. Strategies define why businesses are run.

Software has successfully automated many business processes. Data science automates decisions and strategies via machine learning and reinforcement learning, respectively.

By leveraging our data science consulting services we can help you automate the top two most valuable tiers in the pyramid, to make your organization more efficient and profitable.

The value of reinforcement learning, courtesy of our Reinforcement Learning book.
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.

Selected Case Studies

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

Using Reinforcement Learning to Attack Web Application Firewalls

Introduction Ideally, the best way to improve the security of any system is to detect all vulnerabilities and patch them. Unfortunately this is rarely possible due to the extreme complexity of modern systems. One primary threat are payloads arriving from the public internet, with the attacker using them to discover and exploit vulnerabilities. For this reason, web application firewalls (WAF) are introduced to detect suspicious behaviour. These are often rules based and when they detect nefarious activities they significantly reduce the overall damage.

Helping Modzy Build an ML Platform

Winder.AI collaborated with the Modzy development team and MLOps Consulting to deliver a variety of solutions that make up the Modzy product, a ModelOps and MLOps platform. A summary of this work includes: Developing the Open Model Interface Open-sourcing chassis, the missing link that allows data scientists to build robust ML containers Model monitoring and observability product features MLOps and model management product features The Problem: How to Build An ML Platform Modzy’s goal is to help large organizations orchestrate and manage their machine learning (ML) models.

How To Build a Robust ML Workflow With Pachyderm and Seldon

This article outlines the technical design behind the Pachyderm-Seldon Deploy integration available on GitHub and is intended to highlight the salient features of the demo. For an in depth overview watch the accompanying video on YouTube. Introduction Pachyderm and Seldon run on top of Kubernetes, a scalable orchestration system; here I explain their installation process, then I use an example use case to illustrate how to operate a release, rollback, fix, re-release cycle in a live ML deployment.

Start Your ML Development Project Now

The team at Winder.AI are ready to collaborate with you on your ml 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.