Active Assist Expands Globally: Unleashing Cloud Optimization Insights Worldwide

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Active Assist provides insights and recommendations to help Google Cloud customers proactively optimize their cloud environments for cost, security, performance, and sustainability. If you’re like most customers, you’ve likely encountered these insights and recommendations in the console — either in the Recommendations Hub or embedded on a resource page, like IAM or the VM list pages. (Note that for the rest of this post, we’ll use the word “recommendations” to mean “insights and recommendations.”)
We heard from customers who love recommendations that it should be easier to discover and work with these valuable suggestions across an entire organization, so last year we launched the Recommendations BigQuery export feature to Preview. This allows you to automatically export the recommendations to a BigQuery dataset, which you can then investigate with tools like DataStudio or Looker, and integrate with your company’s existing monitoring solutions and workflows.
Many of you have told us how powerful this feature is, so we’ve been working hard on improvements to make it even more useful. We’re happy to announce that BQ Export 1.0 is now in GA, and that BQ Export 2.0 is in Preview, with new support for Billing Account-level recommendations and cost optimization recommendations that include discount information. This post will cover what’s new with Active Assist BQ Export, as well as a couple other new features of Active Assist.
New features to Active Assist BigQuery Export
Before we dive into the details, if you’re new to Recommendations BQ Export check out our handy getting started guide. It covers the permissions you’ll need and how to set up the export, including instructions for using a service account. It also includes some sample queries and instructions for interacting with the data using Google Sheets. You may also want to check out our prior blog post showing how to optimize your cloud spend with BigQuery and Looker.
Now, on to what’s new!
1. Non-project scoped recommendations
You can now see non-project scoped recommendations, such as billing account, organization, and folder-level recommendations in your export to BigQuery. This ensures that in your export, you are able to see the full portfolio of recommendations that are available to you.
2. Custom contract Pricing
If you have any applicable custom contract pricing for your company, your cost-related recommendations now take those into account (based on your historical costs) in the cost saving calculation when you export them to BigQuery. This will ensure that you have the most accurate cost savings data we have for you and your organization to help you make the best judgment and prioritization when choosing to adopt recommendations. However, you must have the correct permissions first in order to see the custom contract pricing. If the user executing the export to BigQuery does not have the correct permissions, you may continue to see list pricing in your estimated savings. Also, note that the console UI and the Recommender API already have this support.
3. Export now available globally
Customers outside of the US can now set up an export of recommendations to a BigQuery dataset.
Improvements to Active Assist discoverability and usability
1. Global Recommender Viewer role: You can now add the global Recommender Viewer role, which gives you view access to all insights and recommendations available to you, simplifying permission management for new recommenders. Newly launched recommendations will also automatically be added as they become generally available.
2. Dismiss recommendations via Recommender API: You can now directly dismiss recommendations via our API, allowing you to focus on the recommendations you care about and work more efficiently.
3. Shareable links: Another feature that quietly launched recently is the availability of shareable URLs that link to recommendation details in the console. You can access these links in the UI from the upper right of the details panel of any recommendation.

However, these links become even more powerful when combined with Recommendations BigQuery Export. The URLs all have a standard format. This means that within the BigQuery export tables you can easily calculate a new column containing these links using an expression like:
“https://console.cloud.google.com/home/recommendations/view-link/” +
name +
“?project=” +
cloud_entity_idThis example is for project level recommendations (where cloud_entity_type = PROJECT_NUMBER).
For cloud_entity_type = FOLDER, use:
“https://console.cloud.google.com/home/recommendations/view-link/” +
name +
“?folder=” +
cloud_entity_idFor cloud_entity_type = ORGANIZATION, use
“https://console.cloud.google.com/home/recommendations/view-link/” +
name +
“?organizationId=” +
cloud_entity_idThese links can then be embedded in your reports and dashboards, or used by other BigQuery clients.
As a reminder, if you’re interested in setting up reports or dashboards using Recommendations BigQuery Export, take a look at this previous blog post for some great ideas, or you can reference our getting started guide. If you have any feedback, please feel free to reach out to active-assist-feedback@google.com.
Bigbasket: Delivering Groceries Across 25 Cities in India

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When Bigbasket was founded in December 2011, it guaranteed to deliver goods within a one-hour delivery slot of its customers’ choosing or it would refund them 10 percent of their orders. The company also introduced an express service, delivering groceries within 90 minutes of an order being placed.
Bigbasket needed a mapping platform that could help it meet its delivery times, and offer a familiar interface to customers. MediaAgility, a digital consulting company, recommended Google Maps Platform to Bigbasket.
When customers use the Bigbasket mobile app to place orders, they select their locations on a Google Map. The prices and availability of groceries varies according to location, so a customer’s location determines the cost of the order and what can be ordered.
Google Maps Platform Results
- Bigbasket handles more than one million orders per month, and delivers in more than two dozen cities in India
- Bigbasket now has more than four million customers
- Orders are delivered on time, increasing customer loyalty
It is also used to determine driver routes. Bigbasket used the Maps Javascript API to build a web-based app for the company’s backend that tracks all orders and delivery progress. Dispatchers use the Directions API to match drivers with orders and customers, and the Distance Matrix API to get estimate the time of arrival for deliveries. As dispatchers track the progress of deliveries on the map, they can tweak routes as necessary.
“We’ve built Bigbasket from the ground up using Google Maps Platform. It makes sure we have the right customer locations and deliver to them on time. We couldn’t have started Bigbasket without Google Maps. It helps us to be fast and efficient, and make sure our customers get what they’ve ordered quickly,” said Pramod Jajoo, Chief Technology Officer, Bigbasket
10 Reasons that Make Google Cloud the Champion of IaaS

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When you choose to run your business on Google Cloud you benefit from the same planet-scale infrastructure that powers Google’s products such as Maps, YouTube, and Workspace.
We have picked 10 ways in which Google Cloud Infrastructure services outshine alternatives in the market in how they simplify your operations, save money, and secure your data.
1. Custom Machine Types means no wasted resources
Compute Engine offers predefined machine types that you can use when you create a VM instance. A predefined machine type has a preset number of vCPUs and a preset amount of memory; each type is billed at a set price as described on the Compute Engine pricing page.
If predefined machine types don’t meet your needs, you can create a VM instance with a custom number of vCPUs and custom amount of memory, effectively building a custom machine type. Custom machine types are available only for general-purpose machine families. When you create a custom machine type, you are deploying a custom machine type from the E2, N2, N2D, or N1 machine family on GCP. No other leading cloud vendor offers custom machine types so extensively.
Custom machine types are a good idea for workloads that aren’t a good fit for the predefined machine types and for workloads that require more processing power or memory but don’t need all of the upgrades provided by the next machine type level. This translates into lower operating costs. They are also useful for controlling software licensing costs that are based on the number of underlying compute cores.
Jeremy Lloyd, Infrastructure and Application Modernization Lead at Appsbroker, a Google partner:
“Custom machine types coupled with Google’s StratoZone data center discovery tool provides Appsbroker with the flexibility we need to provide cost efficient virtual machines matched to a virtual machine’s actual utilization. As a result, we are able to keep our customers’ operating costs low while still providing the ability to scale as needed.”
2. Compute Engine Virtual Machines are optimized for scale-out workloads
For scale-out workloads, T2D, the first instance type in the Tau VM family, is based on 3rd Gen AMD EPYC processors and leapfrogs VMs for scale-out workloads of any leading public cloud provider today, both in terms of performance and price-performance. Tau VMs offer 56% higher absolute performance and 42% higher price-performance compared to general-purpose VMs from any leading public cloud vendor (source). The x86 compatibility provided by these AMD EPYC processor-based VMs gives you market-leading performance improvements and cost savings, without having to port your applications to a new processor architecture. Sign up here if you are interested in trying out T2D instances in Preview.
For SAP HANA, Google Cloud has demonstrated with SAP how we can run the world’s largest scale-out HANA system in the public cloud (96TB). With such innovation, you are covered as your business grows exponentially.
3. Largest single node GPU-enabled VM
Google is the only public cloud provider to offer up to 16 NVIDIA A100 GPUs in a single VM, making it possible to train very large AI models. Users can start with one NVIDIA A100 GPU and scale to 16 GPUs without configuring multiple VMs for single-node ML training, without crossing the VM layer.
Additionally, customers can choose smaller GPU configurations—1, 2, 4 and 8 GPUs per VM—providing the flexibility to scale their workload as needed.
The A2 VM family was designed to meet today’s most demanding applications—workloads like CUDA-enabled machine learning (ML) training and inference, for example. This family is built on the A100 GPU which offers up to 20x the compute performance compared to the previous generation GPU and comes with 40 GB of high-performance HBM2 GPU memory. To speed up multi-GPU workloads, the A2 VMs use NVIDIA’s HGX A100 systems to offer high-speed NVLink GPU-to-GPU bandwidth that delivers up to 600 GB/s. A2 VMs come with up to 96 Intel Cascade Lake vCPUs, optional Local SSD for workloads requiring faster data feeds into the GPUs and up to 100 Gbps of networking. A2 VMs provide full vNUMA transparency into the architecture of underlying GPU server platforms, enabling advanced performance tuning. Google Cloud offers these GPUs globally.
4. Non-disruptive maintenance means you worry less about planned downtime
Compute Engine offers live migration (non-disruptive maintenance) to keep your virtual machine instances running even when a host system event, such as a software or hardware update, occurs. Google’s Compute Engine live migrates your running instances to another host in the same zone without requiring your VMs to be rebooted. Live migration enables Google to perform maintenance that is integral to keeping infrastructure protected and reliable without interrupting any of your VMs. When a VM is scheduled to be live-migrated, Google provides a notification to the guest that a migration is imminent.
Live migration keeps your instances running during:
- Regular infrastructure maintenance and upgrades
- Network and power grid maintenance in the data centers
- Failed hardware such as memory, CPU, network interface cards, disks, power, and so on. This is done on a best-effort basis; if a hardware component fails completely or otherwise prevents live migration, the VM crashes and restarts automatically and a hostError is logged.
- Host OS and BIOS upgrades
- Security-related updates
- System configuration changes, including changing the size of the host root partition, for storage of the host image and packages
Live migration does not change any attributes or properties of the VM itself. The live migration process transfers a running VM from one host machine to another host machine within the same zone. All VM properties and attributes remain unchanged, including internal and external IP addresses, instance metadata, block storage data and volumes, OS and application state, network settings, network connections, and so on. This has the benefit of reducing operational and maintenance overhead, helps you build a more robust security posture where infrastructure can be consciously revamped from a known good state and minimizes risks for advanced persistent threats.
Refer to Lessons learned from a year of using live migration in production on Google Cloud from the Google engineering team.
5. Trusted Computing: Shielded VMs guard you against advanced, persistent attacks
Establishing trust in your environment is multifaceted, involving hardware and firmware, as well as host and guest operating systems. Unfortunately, threats like boot malware or firmware rootkits can stay undetected for a long time, and an infected virtual machine can continue to boot in a compromised state even after you’ve installed legitimate software.
Shielded VMs can help you protect your system from attack vectors like:
- Malicious guest OS firmware, including malicious UEFI extensions
- Boot and kernel vulnerabilities in the guest OS
- Malicious insiders within your organization
To guard against these kinds of advanced persistent attacks, Shielded VMs use:
- Unified Extensible Firmware Interface (UEFI) BIOS: Helps ensure that firmware is signed and verified
- Secure and Measured Boot: Helps ensure that a VM boots an expected, healthy kernel
- Virtual Trusted Platform Module (vTPM): Establishes root-of-trust, underpins Measured Boot, and prevents exfiltration of vTPM-sealed secrets
- Integrity Monitoring: Provides tamper-evident logging, integrated with Stackdriver, to help you quickly identify and remediate changes to a known integrity state
The Google approach allows customers to deploy Shielded VMs with only a simple click, thereby easing implementation.
6. Confidential Computing encrypts data while in use
Google Cloud was a founding member of the Confidential Computing Consortium. Along with encryption of data in transit and at rest using customer-managed encryption keys (CMEK) and customer-supplied encryption keys (CSEK), Confidential VM adds a “third pillar” to the end-to-end encryption story by encrypting data while in use. Confidential Computing uses processor-based technology that allows data to be encrypted in use while it is being processed in the public cloud. Confidential VM allows you to to encrypt memory in use on a Google Compute Engine VM by checking a single checkbox.
All Confidential VMs support the previously mentioned Shielded VM features under the covers—you can think of Shielded VM as helping to address VM integrity, while Confidential VM addresses the memory encryption aspect which relies on CPU features. With the confidential execution environments provided by Confidential VM and AMD Secure Encrypted Virtualization (SEV), Google Cloud keeps customers’ sensitive code and other data encrypted in memory during processing. Google does not have access to the encryption keys. In addition, Confidential VM can help alleviate concerns about risk related to either dependency on Google infrastructure or Google insiders’ access to customer data in the clear.
See what Google Cloud partners say about Confidential Computing here.
7. Advanced networking delivers full-stack networking and security services with fast, consistent, and scalable performance
Google Cloud’s network delivers low latency, reduces operational costs and ensures business continuity, enabling organizations to seamlessly scale up or down in any region to meet business needs. Our planet-scale network uses advanced software-defined networking and security with edge caching services to deliver fast, consistent, and scalable performance. With 28 regions, 85 zones, and 146 PoPs connected by 16 subsea fiber cables around the world, Google Cloud’s network offers a full stack of layer 1 to layer 7 services for enterprises to run their workloads anywhere. Enterprises can be assured that they have best-in-class networking and security services connecting their VMs, containers, and bare metal resources in hybrid and multi-cloud environments with simplicity, visibility, and control.
Google Cloud’s network has protected customers from one of the world’s largest DDoS attacks at 2.54 Tbps. With our multi-layer security architecture and products such as Cloud Armor, our customers ran their business with no disruptions. Furthermore, our recent integration of Cloud Armor with reCAPTCHA Enterprise adds best-in-class bot and fraud management to prevent volumetric attacks. Cloud Armor is deployed with our Cloud Load Balancer and Cloud CDN, extending the secure benefits at the network edge for traffic coming into Google Cloud so customers have security, performance, and reliability all built in. Furthermore, we are excited to offer Cloud IDS in preview, which was co-developed with security industry leader, Palo Alto Networks, to run natively in Google Cloud.
Our advanced networking capabilities also extends to GKE and Anthos networking. With the GKE Gateway controller, customers can manage internal and external HTTPS load balancing for a GKE cluster or a fleet of GKE clusters with multi-tenancy while maintaining centralized admin policy and control. Unlike other Kubernetes offerings, we offer eBPF dataplane which brings powerful tooling such as Kubernetes network policy and logging to GKE. eBPF is known to kernel engineers as a “superpower” for its unique architecture to load and unload modules in kernel space, and now this capability is built in with Google Cloud networking.
For observability and monitoring, our customers deploy Network Intelligence Center, Google Cloud’s comprehensive network monitoring, verification and optimization platform. With four key modules in Network Intelligence Center, and several more to come, we are working towards realizing our vision of proactive network operations that can predict and heal network failures, driven by AI/ML recommendations and remediation. Network Intelligence Center provides unmatched visibility into your network in the cloud along with proactive network verification. Centralized monitoring cuts down troubleshooting time and effort, increases network security and improves the overall user experience.
8. Regional Persistent Disk for High Availability
Regional Persistent Disk is a storage option that provides synchronous replication of data between two zones in a region. Regional Persistent Disks can be a great building block if you need to ensure high availability of your critical applications as they offer cost-effective durable storage and replication of data between two zones in the same region.
Regional Persistent Disks are also easy to set up within the Google Cloud Console. If you are designing robust systems or high availability services on Compute Engine, Regional Persistent Disks combined with other best practices such as backing up your data using snapshots enable you to build an infrastructure that is highly available and recoverable in a disaster. Regional Persistent Disks are also designed to work with regional managed instance groups. In the unlikely event of a zonal outage, Regional Persistent Disks allow continued I/O through failover of your workloads to another zone. Regional Persistent Disks can help meet zero RPO and near-zero RTO requirements and other stringent SLAs that your critical applications might require by maximizing application availability and protection of data during events such as host/VM failures and zonal outages.
9. Cloud Storage’s single namespace for dual-region and multi-region means managing regional replication is incredibly simple
Similar to how Persistent Disk makes data more available by replicating data across zones, Cloud Storage provides similar benefits for object storage. Cloud Storage within a region is cross-zone by definition, reducing the risk that a zonal outage would take down your application. Cloud Storage adds to this by also providing a cross-region option that can protect against a regional outage and gets your data closer to distributed users. This comes in the form of Dual-region or Multi-region settings for a bucket. These are the simplest to implement cross-region replication offerings in the industry—just a simple button or API call to enable them. In addition to being simple to implement, they offer an added advantage of using a single bucket name that spans regions.
This is unique in the industry. Competitive offerings currently require setting up and managing two distinct buckets, one in each region and they don’t offer the strong consistency properties Cloud Storage offers across regions. Operations and app development are burdened by this design. Google’s single namespace approach dramatically simplifies application development (the app runs on single region or dual/multi-region without any changes), and provides simpler application restarts and testing for DR.
10. Predictive autoscaling
Customers use predictive autoscaling to improve response times for applications with long initialization times or for applications with workloads that vary predictably with daily or weekly cycles. When you enable predictive autoscaling, Compute Engine forecasts future load based on your Managed Instance Group’s history and scales out the MIG’s in advance of predicted load, so that new instances are ready to serve when the load arrives. Without predictive autoscaling, an autoscaler can only scale a group reactively, based on observed changes in load in real time.
With predictive autoscaling enabled, the autoscaler works with real-time data as well as with historical data to cover both the current and forecasted load. Forecasts are refreshed every few minutes (faster than competing clouds) and consider daily and weekly seasonality, leading to more accurate forecasts of load patterns.
For more information, see How predictive autoscaling works and Checking if predictive autoscaling is suitable for your workload.
These are just a few examples of customer-centric innovation that set Google Cloud infrastructure apart. Bring your applications and let the platform work for you.
Get started by learning about your options for migration, or talk to our sales team to join the thousands of customers who have embarked upon this journey.
Acknowledgement
Special thanks to Dheeraj Konidena (Google) for contributing to this article.
A Year of Connecting Brand and Consumers with Google’s Business Messages

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Last June, in the early months of the pandemic, we expanded Business Messages to support all kinds of businesses, from pharmacies and grocery stores to airlines and luxury brands. Then, in December, we announced the ability for small businesses to use the Google Maps app to message with their customers. We knew people would find messaging directly with businesses from Google Search and Maps helpful, but we didn’t know just how valuable it would turn out to be.
Consumers are increasingly eager to use messaging to connect with brands, and businesses across all industries are now building innovative messaging experiences to address that growing need. The demand from consumers is reflected in recent data:
- 45% of users have spent more time on messaging services because of the pandemic
- 85% of consumers would like to message brands directly, up from 65% in 2019
Being able to message a business directly has never been more important. For me personally, there’s nothing more fulfilling than using technology to help people in the moments that matter. After the release of initial COVID-19 vaccines in late 2020, online searches for vaccines reached an all-time high. To help people searching for vaccine eligibility, availability, and appointment booking, Albertsons Companies’ banner pharmacies—like Albertsons, Safeway, and Vons—made this information easily accessible through Google Search and Maps via the “chat” button. This gave people the information they needed, when they needed it.

To be more helpful in moments like these, over the last year, we’ve made Business Messages available globally, in more than 70 languages, and we’ve seen more than 30,000 brands and 200 partners come on board. Major brands like Carrefour, Walmart, and Woolworths have invested in Business Messages to help serve their consumers in new and meaningful ways.
Expanding the conversation between consumers and brands
The retail sector has undergone a transformation since the start of the pandemic. As a result, we know it is critical for digital services to integrate with physical stores. We were able to do just that with Google’s Business Messages, which has been instrumental in helping better serve our customers across 1200+ stores in Europe.
Thomas Rudelle
Global Digital Marketing Director, Carrefour
There were major shifts in consumer behavior during the pandemic, from the way people found and purchased products to the ways they interacted with businesses. Not only did we see higher demand for direct contact with brands, but retail searches also surged. At the end of 2020, retail searches grew at a rate that was more than three times higher than the same period in 2019 (based on Google internal data).
As Business Messages has become more widespread, brands are able to boost both responsiveness and customer satisfaction using the service. Levi’s, for example, surpassed 85% customer satisfaction scores using Business Messages and they discovered that the service drove 30x more store-related questions than web chat.

Many brands have also digitized what were traditionally in-store experiences, especially in high-consideration categories like jewelry. For example, Signet brought its virtual jewelry consultant to Business Messages, offering customers advice and answering queries in a way that’s convenient but still feels personal.We started using Google’s Business Messages pretty early on, and continue to transform and improve our experience. The ability to let customers know whether a product is in stock, and its precise location, is critical to offering a connected and frictionless shopper experience. Of course it also helps reduce the workload on our store and customer hub teams.
Nick Eshkenazi
Chief Digital Technology Officer, Woolworths

As a working mother, these sorts of innovations have made a direct impact in my own life. I find it very helpful to be able to ask—and get real-time answers to—everyday questions using Business Messages, ranging from store hours and product availability to order status and how to make returns. One of my favorite features is the ability to know, in real time, what store wait times are like, and the exact location of the product I’m looking for, saving me precious time when I visit the store.
Business Messages helps people do more with their time in other ways as well. Earlier this year I’d been meaning to change my insurance plan, but kept pushing it off because I didn’t want to get on a phone call. I can now message Geico to update my policy through the agent pretty effortlessly. Similarly, in India, Vi customers can use 24×7 real-time customer service to chat with their AI powered virtual assistant VIC, integrated with Google’s Business Messages, to check billing information, activate packs, add recharges and payments, check balances, and much more—and it all happens seamlessly.

Building a full suite of messaging products
We’re investing in building a full suite of messaging products that enable seamless conversational commerce to drive business results. As Business Messages continues to support brands in establishing their messaging presence on Google, we’re also experimenting with other ways to help them increase their reach and engagement on Search and Display. To accelerate on the digital front, we recently integrated AdLingo, a project built within Area 120, Google’s in-house incubator. This will enable brands to easily transform ads into AI powered, personalized conversations at scale.
For more information on how you can activate Business Messages, please reach us via the contact form on the Business Messages website. Merchants can also read and respond to messages via Google My Business or on the Google Maps app.
Google Meet on Glass: A New Way of Collaborating Teams with Video Meetings in Real-time

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Open beta now available to all Google Workspace customers
Seeing is believing. For many service technicians, trainers, and other frontline workers, the ability to share a real-time view of what they can see with their virtual clients or teams can make all the difference. That’s what we’ve heard from global participants in the closed beta of Google Meet running on Glass Enterprise Edition 2 that we announced last year.
Starting today, we’re making Google Meet on Glass Enterprise Edition 2 (Meet on Glass) more broadly available through an open beta. Any Google Workspace customer around the world can now give their employees, suppliers, and partners greater sight with Glass—using the simple and intuitive Google Meet environment they’re already used to. With Meet on Glass, meeting participants can experience a first-person view of the Glass wearer’s perspective and collaborate with the entire video meeting in real time.

Making it easier to solve hard problems
Customers who’ve been testing Meet on Glass are linking their teams across geographies to collaborate in new ways and solve problems together. In the US, real estate services group CBRE has implemented Meet on Glass to allow employees at job sites to connect with HQ teams and project managers. Connecting the whole team with live video from the frontline is allowing faster decision making and clearer communications between team members.
To be successful, remote assistance via video call must be simple and seamless. CBRE and other early customers have shared that they don’t want their workers to have to become technical experts to use video collaboration in this way. Ease of use—both for Google Meet and for Glass—and speed to join a video meeting are top priorities for them. And with Google Workspace integration, their teams can now join Calendar events directly from Glass with just a few taps. No complex signing in or scanning codes are required; users simply choose from their calendar on Glass to instantly join the meeting.
Getting Google Meet on Glass Enterprise Edition 2
The Meet team is working with the community of Google Workspace partners to enable Google Meet on Glass Enterprise Edition 2 for customers in North America, Europe, and Australia. Customers in Japan can now also get Glass through a first-of-its-kind partnership with NTT DOCOMO, which can provide Meet on Glass directly to its customers in Japan. After extensive testing, NTT DOCOMO chose Google Meet on Glass as the preferred solution for their business customers who want frontline collaboration solutions for their enterprises.
Meet on Glass is one of the ways we’re bringing powerful new video conferencing experiences to customers around the world, regardless of the devices they’re using to connect and collaborate with their teams. When combined with our Google meet hardware and peripherals, the possibilities for real-time connection and problem solving are even greater. And it’s part of our ongoing commitment to creating innovative and immersive meeting experiences that help people feel like they’re working together, not just meeting together.
Sign up now to participate in the Google Meet on Glass Enterprise Edition 2 open beta.
Google’s Intelligent Products Essentials Assist Manufacturers in Product Development Journey

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Expectations for both consumer and commercial products have changed. Consumers want products that evolve with their needs, adapt to their preferences, and stay up-to-date over time. Manufacturers, in turn, need to create products that provide engaging customer experiences not only to better compete in the marketplace, but also to provide new monetization opportunities.
However, embedding intelligence into new and existing products is challenging. Updating hardware is costly, and existing connected products do not have the capability to add new features. Furthermore, manufacturers do not have sufficient customer insights due to product telemetry and customer data silos, and may lack the AI expertise to quickly develop and deploy these features.
That’s why today we’re launching Intelligent Products Essentials, a solution that allows manufacturers to rapidly deliver products that adapt to their owners, update features over-the-air using AI at the edge, and provide customer insights using analytics in the cloud. The solution is designed to assist manufacturers in their product development journeys—whether developing a new product or enhancing existing ones.
With Intelligent Products Essentials, manufacturers can:
- Personalize customer experiences: Provide a compelling ownership experience that evolves over the lifetime of the product. For example, a chatbot that contextualizes responses based on product status and customer profile.
- Manage and update products over-the-air: Deploy updates to products in the field, gather performance insights and evolve capabilities over time with monetization opportunities.
- Predict parts and service issues: Detect operating thresholds, anomalies and predict failures to proactively recommend service using AI, reducing warranty claims, decreasing parts shortages and increasing customer satisfaction.
In order to help manufacturers quickly deploy these use cases and many more, Intelligent Products Essentials provides the following:
- Edge connections: Connect and ingest raw or time-series product telemetry from various device platforms utilizing IoT Core or Pub/Sub and enable deployment and management of firmware over-the-air and machine learning models with Vertex AI at the edge.
- Ownership App Template: Easily build connected product companion apps that work on smartphones, tablets, and computers. Use a pre-built API and accompanying sample app that can incorporate product or device registration, identity management, and provide application behavior analytics using Firebase.
- Product fleet management: Manage, update and analyze fleets of connected products via APIs, Google Kubernetes Engine, and Looker.
- AI services: Create new features or capabilities for your products using AI and machine learning products such as DialogFlow, Vision AI, AutoML, all from Vertex AI.
Enterprise data integration: Integrate data sources such as Enterprise Asset Management (EAM), Enterprise Resource Planning (ERP), Customer Relationship Management (CRM) systems and others using Dataflow and BigQuery.

Intelligent Products Essentials helps manufacturers build new features across consumer, industrial, enterprise, and transportation products. Manufacturers can implement the solution in-house, or work with one of our certified solution integration partners like Quantifi and Softserve.
“The focus on intelligent products that Google Cloud is deploying provides a digital option for manufacturers and users. At its heart, systems like Intelligent Product Essentials are all about decision making. IDC sees faster and more effective decision-making as the fundamental reason for the drive to digitize products and processes. It’s how you can make faster and more effective decisions to meet heightened customer expectations, generate faster cash flow, and better revenue realization,” said Kevin Prouty, Group Vice President at IDC. “Digital offerings like Google’s Intelligent Product Essentials potentially go the last mile with the ability to connect the digital thread all the way through to the final user.”
Customers adopting Intelligent Products Essentials
GE Appliances, a Haier company, are enhancing their appliances using new AI-powered intelligent features to enable:
- Intelligent cooking: Help cook the perfect meal to personal preferences, regardless of your expertise and abilities in the kitchen.
- Frictionless service: Build smart appliances that know when they need maintenance and make it simple to take action or schedule services.
- Integrated digital lifestyle: Make appliances useful at every step of the way by integrating them with digital lifestyle services – for example, automating appliance behaviors according to customer calendars, such as oven preheating or scheduling the dishwasher to run in the late evening.
“Intelligent Products Essentials enhances our smart appliances ecosystem, offering richer consumer habit insights. This enables us to develop and offer new features and experiences to integrate with their digital lifestyle.“ —Shawn Stover, Vice-president Smart Home Solutions at GE Appliances.https://www.youtube.com/embed/zaWAJN8aKOw?enablejsapi=1&
Serial 1, Powered by Harley-Davidson, is using Intelligent Product Essentials to manage and update its next generation eBicycles, and personalize its customers’ digital ownership experiences.
“At Serial 1, we are dedicated to creating the easiest and most intuitive way to experience the fun, freedom, and adventure of riding a pedal-assist electric bicycle. Connectivity is a key component of delivering that mission, and working together to integrate Intelligent Product Essentials into our eBicycles will ensure that our customers enjoy the best possible user experience.”— Jason Huntsman, President, Serial 1.
Magic Leap, an augmented reality pioneer with industry-leading hardware and software, is building field service solutions with Intelligent Products Essentials with the goal of connecting manufacturers, dealers, and customers to more proactive and intelligent service.
“We look forward to using Intelligent Products Essentials to enable us to rapidly integrate manufacturers’ product data with dealer service partners into our field service solution. We’re excited to partner with Google Cloud as we continue to push the boundaries of physical interaction with the digital world.” — Walter Delph, Chief Business Officer, Magic Leap
Intelligent Product Essentials is available today. To learn more, visit our website.
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