Helping Modzy Build an ML Platform

Published

Aug 25, 2021

Author

Dr. Phil Winder

CEO

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

How To Build a Robust ML Workflow With Pachyderm and Seldon

Published

Jul 27, 2021

Author

Enrico Rotundo

Associate Data Scientist

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. Throughout the demo, I showcase how Pachyderm comes in handy with data lineage and automation in a critical scenario.

How We Built an MLOps Platform Into Grafana

Published

Jun 11, 2021

Author

Dr. Phil Winder

CEO

Winder.AI collaborated with Grafana Labs to help them build a Machine Learning (ML) capability into Grafana Cloud. A summary of this work includes:

• Product consultancy and positioning - delivering the best product and experience
• Design and architecture of MLOps backend - highly scalable - capable of running training jobs for thousands of customers
• Tight integration with Grafana - low integration costs - easy product enablement

Grafana’s Need - Machine Learning Consultancy and Development

Grafana Cloud is a successful cloud-native monitoring solution developed by Grafana Labs.

Improving Data Science Strategy at Neste

Published

Aug 7, 2020

Author

Dr. Phil Winder

CEO

Winder.AI helped Neste develop their data science strategy to nudge their data scientists to produce more secure, more robust, production ready products. The results of this work were:

• A unified company-wide data science strategy
• Simplified product development - “just follow the process”
• More robust, more secure products
• Decreased to-market time

Our Client

Neste is an energy company that focuses on renewables. The efficiency and optimization savings that machine learning, artificial intelligence and data science can provide play a key role in their strategy.

Building an Enterprise NLP Platform

Published

Jun 25, 2020

Author

Dr. Phil Winder

CEO

Winder.AI has built a state of the art natural language processing (NLP) platform for a large oil and gas enterprise. This work leveraged a range of cloud-native technologies and sophisticated deep learning-based (DL) machine learning (ML) techniques to deliver a range of applications. Key successes are:

• New NLP workflows developed in hours, not weeks.
• Hugely scalable, from zero to minimise cost to tens of thousands of concurrent connections.
• Enforced corporate governance and unification, without burdening the developer.

Our Client

Our client, a large enterprise in the oil and gas industry, has thousands of Data Scientists working on a range of problems. This company operates throughout the world and is investing heavily in artificial intelligence (AI) to improve the entire organisation.

Google Releases AI Platform with help from Winder.AI

Published

Apr 12, 2019

Author

Dr. Phil Winder

CEO

At their Cloud’s Next 19 conference, Google has announced the launch of an expanded AI platform. For a number of years Google has been expanding it’s portfolio to compete with AI products from Azure and AWS. But this is the first time that the platform can be considered “end-to-end”.

Using Data Science to block hackers

Published

Oct 28, 2018

Author

Dr. Phil Winder

CEO

Executive Summary

Winder.AI was engaged by Bitsensor to research and implement Data Science algorithms that could automate the detection and classification of web attackers. After gathering data, researching a Machine Learning solution and implementing Cloud-Native software, we delivered three new features:

• Tool classification - detect which automated tools were being used to perform the attack
• Attacker grouping - provide the capability of detecting distributed attacks by the same attacker
• Killchain classification - establish the phase of an attack (e.g. reconnaissance, exploitation, etc.)

Client

Bitsensor is a startup in the Netherlands that specializes in protecting public-facing websites and applications. They distribute their web-application firewall product to a range of customers throughout Europe. The goal is to provide an outstanding out-of-the-box experience that can protect exposed services from hackers, with little setup.

Bulding a Cloud-Native PaaS

Published

Oct 25, 2018

Author

Dr. Phil Winder

CEO

Executive Summary

Winder.AI worked with its partner, Container Solutions, to deliver core components of the Weave Cloud Platform-as-a-Service (PaaS).

• Kubernetes and Terraform implementations on Google Cloud Platform
• Delivered crucial billing components to track and bill for per-second usage
• Helped initiate, architect and deliver Weave Flux, a Git-Ops CI/CD enabler

Client

Weaveworks makes it fast and simple for developers and DevOps teams to build and operate powerful containerized applications. They minimize the complexity of operating workloads in Kubernetes by providing automated continuous delivery pipelines, observability and monitoring. Weaveworks also contributes to several open source projects, including Weave Scope, Weave Cortex and Weave Flux. It was one of the first members of the Cloud Native Computing Forum. Founded in 2014, the Company is backed by Google Ventures and Accel Partners. For more information, visit www.weave.works.

How Winder.AI Made Enterprise Cloud Migration Possible

Published

Oct 22, 2018

Author

Dr. Phil Winder

CEO

Executive Summary

• Truly global company, tens of thousands of staff across tens of regions.
• Problem: Colossal amounts of data, lack the computational flexibility to remain competitive.
• Solution: Cloud data platform leveraging Microservices, Serverless object storage and database technologies.
• Benefits: 4x faster, more memory and number of gpus compared to best on-premise hardware. 10x quicker time to market. 10 Petabytes of data.

A very large enterprise in the oil and gas industry asked Winder.AI to help them migrate mission critical workflows to the cloud and create competitive differentiators through the application of Data Science and providing AI consulting.