List of Tecton Platform Customers
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Since 2010, our global team of researchers has been studying Tecton Platform customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Tecton Platform for ML and Data Science Platforms from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Tecton Platform for ML and Data Science Platforms include: HelloFresh, a Germany based Retail organisation with 19595 employees and revenues of $7.61 billion, Atlassian, a Australia based Professional Services organisation with 12157 employees and revenues of $4.36 billion, Tide, a United Kingdom based Professional Services organisation with 1000 employees and revenues of $120.0 million and many others.
Contact us if you need a completed and verified list of companies using Tecton Platform, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The Tecton Platform customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight | Insight Source |
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Atlassian | Professional Services | 12157 | $4.4B | Australia | Tecton | Tecton Platform | ML and Data Science Platforms | 2021 | n/a | In 2021, Atlassian implemented the Tecton Platform as an enterprise feature platform within its ML infrastructure, using the Tecton Platform to support predictive experiences such as content field recommendations in Jira and Confluence. The implementation is categorized under ML and Data Science Platforms and was positioned to standardize how product teams create, serve, and reuse features across Atlassian’s product set. The deployment focused on feature store capabilities, feature pipelines, and feature engineering workflows to accelerate model-ready data delivery. Teams configured Tecton Platform feature pipelines to automate offline and online feature materialization, and the platform was used to streamline feature versioning and feature retrieval patterns that feed model training and serving workflows. Operational coverage spanned multiple product teams responsible for Jira and Confluence recommendation experiences, with the Tecton Platform integrated into those product ML workflows to provide consistent feature semantics. The rollout reduced feature development time from months to days, increased data consistency across model training and serving, and reclaimed engineering FTEs that had been maintaining an internal feature store. Governance centered on centralizing feature definitions and standardizing feature compute and storage processes to improve consistency and accelerate deployment cadence. Outcomes reported include improved model accuracy and faster deployment speed across product teams, with the Tecton Platform serving as the authoritative feature management layer within Atlassian’s ML and Data Science Platforms stack. | |
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HelloFresh | Retail | 19595 | $7.6B | Germany | Tecton | Tecton Platform | ML and Data Science Platforms | 2022 | n/a | In 2022, HelloFresh adopted the Tecton Platform as a foundational feature-store component to standardize feature engineering across marketing, supply chain and finance teams. The Tecton Platform, categorized as ML and Data Science Platforms, was used to power Morpheus, a customer-level prediction system deployed across multiple geographies. The implementation configured Tecton Platform core feature-store capabilities, including centralized feature definitions, offline batch feature materialization and low-latency online feature serving to support production scoring. Teams implemented standardized feature engineering pipelines and feature versioning to increase model reuse and accelerate model rollout. Tecton Platform was integrated with Morpheus model training and inference pipelines to provide consistent feature inputs for production models, supporting both training-time feature retrieval and real-time serving for customer-level predictions. Operational coverage extended across marketing, supply chain and finance functions and spanned multiple regional deployments to unify feature semantics across geographies. The adoption enabled 1,360 models in production and delivered faster model rollout across teams, explicitly improving model reuse and time-to-production. Governance measures included a central feature registry, discoverability and lineage controls, and access policies to enforce consistent feature definitions across business functions. | |
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Tide | Professional Services | 1000 | $120M | United Kingdom | Tecton | Tecton Platform | ML and Data Science Platforms | 2022 | n/a | In 2022, Tide deployed the Tecton Platform to power real time machine learning for finance use cases across its UK platform. The work centered on automated credit risk assessment and transaction fraud detection, positioning Tecton Platform within the ML and Data Science Platforms category for operational ML workloads. The implementation focused on real time feature engineering and feature store capabilities, production feature pipelines, and model serving to support high frequency scoring for credit and fraud decisions. Tide configured feature pipelines and model inference paths to standardize feature definitions, enable online feature retrieval, and accelerate model promotion from development to production. Operational coverage included Tide’s finance and risk functions across the United Kingdom, with the platform used to operationalize models for credit decisioning and fraud screening. Integrations were scoped to feed transaction streams and decisioning pipelines, and the Tecton Platform supported continuous model iteration and deployment within existing ML lifecycle workflows. Tide reported roughly 2x more models in production and 50 percent faster time to production after adopting the Tecton Platform. Reported business outcomes included a roughly 50 percent increase in approval rates for credit with a roughly 5 percent reduction in losses, and 20 percent fewer blocked transactions while improving fraud signal quality. |
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