Products & services

Our products and services help to solve your data science challenges

The starting point of our projects is to assess the current data maturity level of the process. Once the data needs and challenges of your company are clear, we start building tailor-made solutions to your use-case. By setting up data infrastructure and empowering or creating your own data science team, we make integration and adoption of production-ready solutions possible and future-proof.

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Machine Learning Audit

Companies
Are you curious how data and machine learning mature your company is? Our ML audit gives a (repetitive) external review of the current maturity level and actionable advice on how to move towards using ML in your company.

Venture Capitalists
You want to invest in a start-up or scale-up, however you have little information about their current data maturity level. The ML audit gives clear insights into the ML capabilities of the current team, the ML infrastructure and the future ML scalability.

Two days on site review with interviews, architecture scans and code reviews
Audit report including SWOT analysis and red flags
Deep dives on technical ML aspects
Deep dives on the business value of ML and possible use cases

Swishfund | SnappCar | Finqle |

Machine Learning Engine (MLE)

You want to use machine learning or AI in your company, however the real challenge is to get production-ready solutions? Our ML Engine is a powerful platform where predictive models run in production.

The engine
The MLE is tailor-made and completely build to function best in your use-case. A fully managed platform that will be integrated into your own technology stack. The engine can make real-time predictions and connects for example to your website or database. This way, predictions and results can be used immediately in every process in your organization.

Feedback loop
From the start of the project, we work together closely with your business-team and/or AI team in every step of the process. Creating a feedback loop to enable continuous improvement of the MLE over time and be sure we are still on the right track.

Machine Learning Engineers
Our team consists of highly skilled Machine Learning Engineers, combining data science and data engineering to build the MLE’s in production. Next to their technical knowledge, they are passionate about explaining the solutions in an understanding way.

Vlucht-Vertraagd | Wonderkind |

Machine Learning Infrastructure

You have a team of data scientists, but struggle to get their awesome models to an actual production state? We are there to help! We build a stable and future-proof data science infrastructure, to enable your (future) data scientists to put models in production. Because we believe that the combination of data science and data engineering unlocks the true value of AI and Machine Learning.

Quin | Goboony | Van Eeghen |

Data Science Control System (DSCS)

The Git of Data Science. Track changes and performance of your ML models and applications with DSCS. Enabling real-time visual insights into the performance, uptime and overall health of your ML solutions. Open the black-box of Data Science models.

Gather metrics from data pipelines, learning engines, API’s, models and final predictions
Keep track of your model performance, accuracy and overall health
Makes use of popular logging methods and services like Google Stackdriver

Enjins Training Program

You have a team of data scientists but struggle to get ML applications into production? Or you want to inspire your business and become Data Scientist/Engineer for a day. Ask us for training programs, to understand the full potential of Data Science.

Creating data pipelines to get your ML application into production
Logging and monitoring of your data pipeline and ML model
Introduction to cloud architectures and containers (Docker and Kuberneters)
Create your first API

Whether you are thinking about expanding your existing team or hiring your first data analyst, scientist or engineer. We think along with you to hire the (combination of) people that fit best with your future goal and organisation.

Wonderkind

Dynamic Pricing

Machine learning is rapidly revolutionizing different sectors, including human resources. Enjins developed the fully automated Wonderkind Predictive Learning Engine, enabling Dynamic Pricing for Wonderkind campaigns.

Wonderkind case

Getting Machine Learning Ready

Enjins helps Finqle to become AI-ready. By realizing a setup of their analytics infrastructure and connecting all relevant data sources, Finqle is ready for smarter fraud prediction and payment anomaly detection. Working towards the goal of risk reduction.

Finqle Case

Data Science Infrastructure

Goboony is the fastest growing European sharing platform for campers. Enjins developed their data science infrastructure and is building towards Goboony’s recommendation engine to optimize supply and demand. Goboony Case

Get in touch

Curious to find out what machine learning can do for you?

Don’t hesitate to fill out the contact form and get in touch.