Tecton

Tide Deploys Models 2x Faster with Tecton’s Feature Platform

  • Gaetan Castelein
By
Published: March 4, 2021
Last updated: October 17, 2023

50% improvement

Time to deploy new models to production decreased to just 1 month from 2 – 4 months.

9 months

Engineering time recovered from continuing to build internal feature store.

3 engineers

Resources repurposed from maintaining internal feature store.

Tide is a UK-based mobile-first banking platform for small and medium-sized enterprises, offering business bank accounts and services to over 300,000 members. Tide thrives on making data-driven decisions to help their customers save time and money. After facing challenges building production ML data pipelines and an internal feature store, Tide’s dedicated team of data scientists and engineers implemented the Tecton enterprise feature store to build and deploy ML features. As a core component of Tide’s ML stack, Tecton enables a number of ML use cases including fraud detection, risk mitigation, and real-time invoice matching for transactions. With Tecton, Tide accelerated the time to build models, tripled the number of features used per model, and saved the significant engineering time and headcount required to build and maintain an internal feature store.

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Interested in trying Tecton? Leave us your information below and we’ll be in touch.​

Unfortunately, Tecton does not currently support these clouds. We’ll make sure to let you know when this changes!

However, we are currently looking to interview members of the machine learning community to learn more about current trends.

If you’d like to participate, please book a 30-min slot with us here and we’ll send you a $50 amazon gift card in appreciation for your time after the interview.

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or

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Interested in trying Tecton? Leave us your information below and we’ll be in touch.​

Unfortunately, Tecton does not currently support these clouds. We’ll make sure to let you know when this changes!

However, we are currently looking to interview members of the machine learning community to learn more about current trends.

If you’d like to participate, please book a 30-min slot with us here and we’ll send you a $50 amazon gift card in appreciation for your time after the interview.

CTA link

or

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