AI Buyer Insights:

Cantor Fitzgerald, a Kyriba Treasury customer evaluated GTreasury

Citigroup, a VestmarkONE customer evaluated BlackRock Aladdin Wealth

Swedbank, a Temenos T24 customer evaluated Oracle Flexcube

Michelin, an e2open customer evaluated Oracle Transportation Management

Westpac NZ, an Infosys Finacle customer evaluated nCino Bank OS

Moog, an UKG AutoTime customer evaluated Workday Time and Attendance

Wayfair, a Korber HighJump WMS customer just evaluated Manhattan WMS

Cantor Fitzgerald, a Kyriba Treasury customer evaluated GTreasury

Citigroup, a VestmarkONE customer evaluated BlackRock Aladdin Wealth

Swedbank, a Temenos T24 customer evaluated Oracle Flexcube

Michelin, an e2open customer evaluated Oracle Transportation Management

Westpac NZ, an Infosys Finacle customer evaluated nCino Bank OS

Moog, an UKG AutoTime customer evaluated Workday Time and Attendance

Wayfair, a Korber HighJump WMS customer just evaluated Manhattan WMS

Catawiki Data, Technology Stack, and Enterprise Applications
ERP Financial Management
Vendor
Previous System
Application
Category
Market
VAR/SI
When
Live
Insight
Workday Legacy Workday Financial Management ERP Financial ERP Financial Management n/a 2016 2017
Expense Management ERP Financial Management 2016 2017
AI Development
Vendor
Previous System
Application
Category
Market
VAR/SI
When
Live
Insight
Domino Data Lab Legacy Domino Data Science Platform ML and Data Science Platforms AI Development n/a 2016 2017
In 2016 Catawiki implemented Domino Data Science Platform as part of its ML and Data Science Platforms strategy, arming business users with insights that help them make smarter, faster decisions. The deployment explicitly embedded machine learning to optimize the company recommendation engine, product pricing predictions, marketing promotions, lead scoring and cancellation predictions. The Domino Data Science Platform provided a centralized environment for model development, experimentation, reproducible runs and model deployment to production, enabling data scientists to iterate and package models for operational use. Functional implementation focused on operationalizing predictive models that feed recommendation logic, dynamic pricing predictions, promotional targeting and customer cancellation forecasting. Operational scope covered cross functional business users and analytics teams in merchandising and recommendations, pricing, marketing and customer operations, delivering model driven insights into decision workflows. Governance and workflow changes emphasized reproducible experiments, model lifecycle tracking and closer collaboration between data science and business stakeholders to accelerate model handoff and operationalization. Catawiki used Domino Data Science Platform to arm business users with actionable insights and to embed machine learning across core commerce and customer retention functions, aligning ML and Data Science Platforms capabilities with product, marketing and operations priorities.
Analytics and BI
Vendor
Previous System
Application
Category
Market
VAR/SI
When
Live
Insight
Google Legacy Google Looker Analytics and BI Analytics and BI n/a 2016 2016
In 2016 Catawiki implemented Google Looker to centralize Analytics and BI capability and provide a single semantic layer for cross‑department reporting and experiment analysis. The deployment served as the core reporting platform for the Data Science Insights team, enabling dashboards, ad hoc analysis, and strategic recommendations to all departments. Google Looker was configured as a semantic modeling and dashboarding platform, with LookML-driven explores and curated dashboards used for recurring reporting and self-service analytics. The implementation included scheduled deliveries and interactive dashboards to support A/B experiment analysis and product performance monitoring, aligning with typical Analytics and BI functional workflows. The implementation integrated directly with Google BigQuery as the primary data warehouse, with data pipelines coordinated by Airflow and Dataform for model build and transformation. Operational tooling included Python for data engineering, Git and GitHub for version control of LookML and transformation code, and Google Analytics for web event and traffic instrumentation feeding the BI layer. Governance used Git-backed model development and code review workflows to control semantic definitions and metric consistency, while the Data Science Insights team managed model releases and dashboard lifecycle. This architecture centralized metric definitions in Google Looker, supported cross-functional access to curated insights, and underpinned experiment design and analysis across Catawiki.
Data Warehouse Analytics and BI 2016 2016
Collaboration
Vendor
Previous System
Application
Category
Market
VAR/SI
When
Live
Insight
Collaboration Collaboration 2011 2011
Content Management
Vendor
Previous System
Application
Category
Market
VAR/SI
When
Live
Insight
Web Content Management Content Management 2019 2019
CRM
Vendor
Previous System
Application
Category
Market
VAR/SI
When
Live
Insight
Customer Experience CRM 2015 2015
Customer Experience CRM 2020 2020
Marketing Analytics CRM 2017 2017
Marketing Automation CRM 2016 2016
IT Asset Management
Vendor
Previous System
Application
Category
Market
VAR/SI
When
Live
Insight
Hardware Asset Management (HAM) IT Asset Management 2021 2021
PaaS
Vendor
Previous System
Application
Category
Market
VAR/SI
When
Live
Insight
Transactional Email PaaS 2015 2015
IaaS
Vendor
Previous System
Application
Category
Market
VAR/SI
When
Live
Insight
Application Hosting and Computing Services IaaS 2021 2021
Content Delivery Network IaaS 2016 2016
CyberSecurity
Vendor
Previous System
Application
Category
Market
VAR/SI
When
Live
Insight
Identity and Access Management (IAM) CyberSecurity 2021 2021
IT Decision Makers and Key Stakeholders at Catawiki
First Name Last Name Title Function Department Email Phone
No data found
Apps Being Evaluated by Catawiki Executives
Date Company Status Vendor Product Category Market
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FAQ - APPS RUN THE WORLD Catawiki Technographics

Catawiki is a Professional Services organization based in Netherlands, with around 600 employees and annual revenues of $102.0 million.

Catawiki operates a diverse technology stack with applications such as Workday Financial Management, Domino Data Science Platform and Google Looker, covering areas like ERP Financial, ML and Data Science Platforms and Analytics and BI.

Catawiki has invested in cloud applications and AI-driven platforms to optimize efficiency and growth, collaborating with vendors such as Workday, Domino Data Lab and Google.

Catawiki recently adopted applications including Workwize IT Asset Management in 2021, Google Cloud Platform (GCP) in 2021 and Okta Identity Cloud in 2021, highlighting its ongoing modernization strategy.

APPS RUN THE WORLD maintains an up-to-date database of Catawiki’s key decision makers and IT executives, available to Premium subscribers.

Our research team continuously updates Catawiki’s profile with verified software purchases, vendor relationships, and digital initiatives identified from public and proprietary sources.

Subscribe to APPS RUN THE WORLD to access the complete Catawiki technographics profile, including detailed breakdowns by category, vendor, and IT decision makers.