List of Google TensorFlow Customers

Google

1600 Amphitheatre Parkway,
Mountain View, 94043, CA,
United States

https://www.google.com/

1 650-253-0000

Communications

190820

$402.8B

Since 2010, our global team of researchers has been studying Google TensorFlow 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 Google TensorFlow 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 Google TensorFlow for ML and Data Science Platforms include: Elevance Health, formerly Anthem, Inc, a United States based Insurance organisation with 104900 employees and revenues of $171.34 billion, Intel, a United States based Manufacturing organisation with 88400 employees and revenues of $53.10 billion, The Coca-Cola Company, a United States based Consumer Packaged Goods organisation with 69700 employees and revenues of $47.06 billion, Airbnb, a United States based Professional Services organisation with 7300 employees and revenues of $11.10 billion, Twitter, Inc., a United States based Media organisation with 7500 employees and revenues of $5.08 billion and many others.

Contact us if you need a completed and verified list of companies using Google TensorFlow, 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 Google TensorFlow 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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Customer	Industry	Empl.	Revenue	Country	Vendor	Application	Category	When	SI	Insight Source
Airbnb	Professional Services	7300	$11.1B	United States	Google	Google TensorFlow	ML and Data Science Platforms	2018	n/a	In 2018 Airbnb began using Google TensorFlow within its ML and Data Science Platforms work to improve photo intelligence for listings. The implementation focused on image classification and object detection workflows applied to listing photos to support listing quality verification and amenity discovery. For image classification Airbnb retrained a deep neural network, ResNet50, on a dataset of a few million images using an AWS P2.8xlarge instance with Nvidia 8 core K80 GPUs, sending a batch of 128 images to eight GPUs per training step. Training used Google TensorFlow as the backend in a parallel training topology, and the model was compiled after parallelizing to enable successful execution. To accelerate convergence the team initialized model weights with pre trained ImageNet weights loaded via keras.applications.resnet50.ResNet50. The best ResNet50 model was obtained after three epochs of training which ran for about six hours, after which the model began to overfit and validation performance stopped improving. These training observations guided stop criteria and weight initialization choices for subsequent experiments. Airbnb also evaluated object detection by running a pre trained Faster R-CNN model trained on the Open Images Dataset and using the TensorFlow Object Detection API for quick evaluations. The detector produced bounding boxes for items such as Window, Door and Dining Table in listing photos, showing the capability to localize amenity objects. Operational scope covered listing photo pipelines to enable automated verification of host listings and to make it easier for guests to find homes with specific amenity needs. Governance and rollout plans include creating Airbnb specific amenity labels and retraining the Faster R-CNN model on those labels, integrating algorithm detected amenities into listing quality assessment and search workflows.
Altair Engineering	Professional Services	3300	$666M	United States	Google	Google TensorFlow	ML and Data Science Platforms	2023	n/a	In 2023, Altair Engineering implemented Google TensorFlow within its ML and Data Science Platforms tooling to build a user-assisting feature for the HyperWorks simulation environment. The work was performed by the HyperWorks core development team in Troy, MI, and focused on applying sequence modeling to in-application user behavior data to support engineering workflows. The implementation used deep learning sequence modeling techniques, specifically recurrent neural networks, to model user command history data and predict the next command in a sequence. Development artifacts and runtime components were built using Python and Pandas with model training and inference executed in Google TensorFlow, while the final inference output was surfaced through a GUI component inside the simulation client. Integration concentrated on coupling TensorFlow model inputs to HyperWorks command history telemetry and embedding the inference endpoint into the simulation GUI so that predictions could be called inline during user sessions. The effort impacted software engineering and product development functions within the HyperWorks team, aligning model training, validation, and deployment workflows with application telemetry and UI event streams. Governance and delivery followed an iterative prototyping approach led by the HyperWorks core development team during the internship period, with test data derived from historical command sequences and model validation performed against held out sequences. The implementation positioned Google TensorFlow as the ML runtime in Altair Engineering ML and Data Science Platforms for next-command prediction use cases in simulation software.
Anaplan	Professional Services	2200	$950M	United States	Google	Google TensorFlow	ML and Data Science Platforms	2018	n/a	In 2018, Anaplan implemented Google TensorFlow to embed machine learning capabilities into its Connected Planning platform as part of a strategic move into ML and predictive planning. The deployment used TensorFlow models running on Google Cloud Machine Learning Engine to add predictive forecasting and optimization capabilities to Anaplan’s planning workflows. Anaplan engaged Google Cloud Professional Services to identify required datasets and accelerate model development, resulting in two customer prototype builds that used custom TensorFlow models. The implementation focused on predictive planning and inventory optimization workflows, aligning TensorFlow model training and inference with Anaplan’s Connected Planning use cases and complementing existing mathematical optimization capabilities such as Optimizer. Integrations implemented during the proofs of concept included ingestion of historical sales, inventory, and promotions data, point of sale feeds, external signals such as customer demographics and weather from BigQuery Public Datasets, and cross‑market sales and health data. The first POC ran on 10 percent of a large beverage customer’s U.S. market over two months, and a second POC for a CPG customer evaluated short term forecasting across three brands over six weeks, demonstrating the operational scope was customer program level and focused on planning and supply chain decisioning. Governance and rollout emphasized rapid proofs of concept to discover high value use cases, a collaborative delivery model with Google Cloud Professional Services to avoid false starts, and an ongoing partnership model to provide continued ML expertise and platform updates. The approach prioritized fast time to market for machine learning solutions and selective operationalization of models that proved relevant to enterprise customers. Outcomes reported by Anaplan and Google include identification of almost $2 million in achievable savings for a large beverage customer through local retail inventory optimization, described as a 15 percent uplift versus other methods, and more than $4 million in potential improvements for a CPG customer from improved forecasting and inventory decisions. Anaplan stated that running Google TensorFlow models on Google Cloud Machine Learning Engine made the company more competitive in an AI driven market and reduced the risk and cost of tactical decision making for its customers.
	Professional Services	1000	$990M	United States	Google	Google TensorFlow	ML and Data Science Platforms	2022	n/a
	Professional Services	150	$18M	Canada	Google	Google TensorFlow	ML and Data Science Platforms	2020	n/a
	Professional Services	90	$35M	United States	Google	Google TensorFlow	ML and Data Science Platforms	2022	n/a
	Professional Services	150	$50M	United States	Google	Google TensorFlow	ML and Data Science Platforms	2022	n/a
	Insurance	104900	$171.3B	United States	Google	Google TensorFlow	ML and Data Science Platforms	2016	n/a
	Professional Services	50	$5M	United States	Google	Google TensorFlow	ML and Data Science Platforms	2019	n/a
	Manufacturing	88400	$53.1B	United States	Google	Google TensorFlow	ML and Data Science Platforms	2016	n/a

Showing 1 to 10 of 22 entries

Buyer Intent: Companies Evaluating Google TensorFlow

ARTW Buyer Intent uncovers actionable customer signals, identifying software buyers actively evaluating Google TensorFlow. Gain ongoing access to real-time prospects and uncover hidden opportunities. Companies Actively Evaluating Google TensorFlow for ML and Data Science Platforms include:

Visa, a United States based Banking and Financial Services organization with 28800 Employees

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