Tecton reports record demand for its machine learning

SAN FRANCISCO, July 12 08, 2022 (GLOBE NEWSWIRE) — Tecton, the leading ML feature platform company, today announced record demand for its platform and Feast, the most popular open source feature store:

  • The company’s annual recurring revenue (ARR) nearly tripled from fiscal 2021 to fiscal 2022, and its annual ARR growth rate accelerated to more than 180% in the last fiscal quarter that ended in April 2022.
  • Its customer base has more than quintupled over the past 12 months. Clients span all major Fortune 500 verticals as well as leading tech innovators like Convoy, HelloFresh, Plaid and Tide
  • The number of monthly active users for Feast has grown over 5 times a year to over 800 monthly active users

“We believe that any business should be able to develop reliable operational ML applications and easily adopt real-time capabilities, regardless of the use case at hand or the engineering resources of the staff. This new funding will help us expand and strengthen Tecton’s Feature Platform for ML and the Feast open-source feature store, enabling organizations of all sizes to build and deploy automated ML in applications and processes live, customer-facing, quickly and at scale,” said Mike Del Balso, co-founder and CEO of Tecton.

Tecton was founded by the creators of Uber’s Michelangelo platform to make world-class ML accessible to all businesses. Tecton is a fully managed ML feature platform that orchestrates the full feature lifecycle, from transformation to live service, with enterprise-grade SLAs. The platform enables ML engineers and data scientists to automate raw data transformation, generate training datasets, and provide functionality for large-scale online inference. Whether organizations are building pipelines in batches or already including real-time functionality in their ML initiatives, Tecton solves the many data and engineering hurdles that keep development times sky high and, in many cases, prevent predictive applications to achieve production.

4 Components of Tecton’s Feature Platform

  • Feature Repository: Tecton’s Feature Repository allows users to define features in python files using a declarative framework and manage those features through a git repository.
  • Feature pipelines: Tecton automatically orchestrates data pipelines to continuously process and transform raw data into features.
  • Feature Store: Tecton stores present values ​​consistently across training and service environments. Users can easily retrieve historical features to train models or serve the latest features for online inference.
  • Monitoring: Tecton enables teams to continuously monitor data pipelines, supporting latency and processing costs, allowing them to automatically troubleshoot issues and control the quality, cost and reliability of ML applications .

Company milestones

  • Tecton emerged from stealth with its features platform for ML in private beta with paying customers and announced $25 million in seed and Series A funding co-led by Andreessen Horowitz and Sequoia
  • Tecton became a major contributor to Feast and began allocating technical and financial resources to the project to develop advanced capabilities.
  • Tecton released its feature platform and announced $35 million in Series B funding co-led by previous investors Andreessen Horowitz and Sequoia


  • Tecton has been named a Cool Vendor in Enterprise AI Operationalization and Engineering by Gartner, Inc.[1]
  • Tecton has released low-latency streaming pipelines for ML, enabling data teams to build and deploy real-time models in hours instead of months
  • Feast 0.10, the first feature store that can be deployed locally in minutes without dedicated infrastructure, is released
  • Tecton launched its apply() event series on Data Engineering for Applied ML, with over 8,000 registered attendees


  • Tecton has partnered with Databricks and Snowflake to accelerate ML application delivery and both have become strategic investors. Last month, Tecton was named Databricks’ ML/AI Partner of the Year and Snowflake’s Emerging Technology Partner of the Year.
  • Tecton has partnered with Redis to enable a low-latency, highly scalable, and cost-effective service of features to support operational ML applications
  • Tecton hosted two apply() events with over 10,000 registered attendees combined

Tecton Raises $100M in Series C Funding
Today, Tecton also announced that it has raised $100 million in Series C funding, bringing the total raised to $160 million. This round was led by new investor Kleiner Perkins with participation from strategic investors Databricks and Snowflake Ventures, previous investors Andreessen Horowitz and Sequoia Capital and new investors Bain Capital Ventures and Tiger Global. Tecton plans to use the money to deliver more customer value and scale engineering and go-to-market teams.

“We expect the software we use today to be highly personalized and intelligent. While ML makes this possible, it remains far from reality because the enabling infrastructure is extremely difficult to build for all but the most advanced companies,” said Bucky Moore, Partner, Kleiner Perkins. “Tecton makes this infrastructure accessible to all teams, allowing them to build ML applications faster. As this continues to accelerate their growth trajectory, we are proud to partner with Mike, Kevin and their team to pioneer and lead this exciting new space.

“Investing in Tecton is a natural fit for Databricks Ventures as we seek to expand the Lakehouse ecosystem with best-in-class solutions and support companies that align with our mission to simplify and democratize data and AI. “said Andrew Ferguson, head of Databricks Enterprises. “We are excited to deepen our partnership with the Tecton team and look forward to providing continued innovation to our mutual customers.”

“Together, Tecton and Snowflake enable data teams to securely and reliably store, process, and manage the full lifecycle of production ML functionality in Snowflake, empowering users in data science teams, engineering and analysts to collaborate and work from a single source of truth in data,” said Stefan Williams, vice president of corporate development and Snowflake Ventures at Snowflake. “This investment expands our partnership and is the latest example of Snowflake’s commitment to helping our customers get the most out of their data effortlessly.

Additional Resources

About Tecton
Tecton’s mission is to make world-class ML accessible to every business. Tecton’s Feature Platform for ML enables data scientists to turn raw data into production-ready features, the predictive signals that power ML models. The founders created the Uber Michelangelo ML platform, and the team has extensive experience building data systems for industry leaders like Google, Facebook, Airbnb, and Uber. Tecton is backed by Andreessen Horowitz, Bain Capital Ventures, Kleiner Perkins, Sequoia Capital and Tiger Global as well as strategic investors Databricks and Snowflake Ventures. Tecton is the main contributor and author of Feast, the leading open source feature store. For more information, visit https://www.tecton.ai or follow @tectonAI.

Media and analyst contact:
Amber Rowland

[1] Gartner, “Cool Vendors in Enterprise AI Operationalization and Engineering”, Chirag Dekate, Farhan Choudhary, Soyeb Barot, Erick Brethenoux, Arun Chandrasekaran, Robert Thanaraj, Georgia O’Callaghan, 27 April 2021 (report available to Gartner subscribers here: https://www.gartner.com/doc/4001037)

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Sherry J. Basler