Google has launched a cloud based contact center software which uses artificial intelligence (AI) to improve the customer experience and provide real-time insights for agents. Announced in July 2018, this product adds three core AI functionalities to the contact center software tool belt with its Dialogflow feature: virtual agents, AI assistance for human agents, and contact center analytics. Google’s product streamlines inbound and outbound communications by…
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Microsoft Azure
Score 8.6 out of 10
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Microsoft Azure is a cloud computing platform and infrastructure for building, deploying, and managing applications and services through a global network of Microsoft-managed datacenters.
$29
per month
Pricing
Google Cloud Contact Center AI
Microsoft Azure
Editions & Modules
No answers on this topic
Developer
$29
per month
Standard
$100
per month
Professional Direct
$1000
per month
Basic
Free
per month
Offerings
Pricing Offerings
Google Cloud Contact Center AI
Microsoft Azure
Free Trial
No
Yes
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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The free tier lets users have access to a variety of services free for 12 months with limited usage after making an Azure account.
Well suited for sites where the product is hardware because with those if there are any questions then the site could help eliminate having to contact the company directly and waiting for answers days later. This would be suited for products as the answer could be given and the more complex questions would be directed to the company.
In terms of cloud computing, Microsoft Azure is the only comprehensive result the company offers. Regardless of how big or small an organization is, it can make use of this system. As a cyber-security professional, this is your best option for data management. A business that wants to minimize capital expenditures can use Microsoft Azure. Many Microsoft services accept it. People with little or no knowledge of cloud computing may find it impossible. It isn’t the solution for companies that don’t want to risk having only one platform and infrastructure vendor.
Google Cloud Contact Center AI is based on the same foundation infrastructure and services as Google Assistant, therefore, it is robust and flexible. The APIs are very well built and documented as well. Any newbie can start using the service with a very little learning curve.
Seamless integrations are also a great add-on. Google makes sure that Contact Center AI service integrates well with leading customer service platforms which helps any user to use only the required functionalities from Contact Center AI and meanwhile use any other primary platform.
Robust documentation which is always alive and is updated within no time is of great help! Google makes sure its end customers know what to do where and when in clear plain text and any issues/ bugs are also documented.
Azure simply provides end to end life cycle. Starting from the development to automated deployment, you will find [a] bunch of options. Custom hook-points allow [integration] on-premise resources as well.
Excellent documentation around all the services make it really easy for any novice. Overall support by [the] community and Azure Technical team is exceptional.
BOT Services, Computer Vision services, ML frameworks provide excellent results as compare to similar services provided by other giants in the same space.
Azure data services provide excellent support to ingest data from different sources, ETL, and consumption of data for BI purpose.
In our experience, Azure Kubernetes Survice was difficult to set up, which is why we used Kubernetes on top of VMs.
Azure REST API is a bit difficult to use, which made it difficult for us to automate our interactions with Azure.
Azure's Web UI does a good job of showing metrics on individual VMs, but it would be great if there was a way to show certain metrics from multiple VMs on one dashboard. For example, hard drive usage on our database VMs.
We are happy with the implementation and functionality of the software and associated systems. In general, unless something better can replace this system we intend on continuing. We think the ease of systems implementation and integration adds value and substantiates the use and excellent functionality of the product and associated services.
Moving to Azure was and still is an organizational strategy and not simply changing vendors. Our product roadmap revolved around Azure as we are in the business of humanitarian relief and Azure and Microsoft play an important part in quickly and efficiently serving all of the world. Migration and investment in Azure should be considered as an overall strategy of an organization and communicated companywide.
Generally intuitive and easy to learn. I would like more guides but the learning curve is rather quick and makes the software rather an easy study for the average user. Generally, the support and functionality of the software make for a generally good outcome and easy implementation of the software and user experience.
Microsoft Azure's overall usability has been better than expected. Often times vendors promise the world, only to leave you with a run-down town. Not the case with our experience. From an implementation perspective, all went perfect, and from the user-facing experience we have had no technical issues, just some learning curve issues that are more about "why" than "how"
Support is easy with all the knowledge base articles available for free on the web. Plus, if you have a preferred status you can leverage their concierge support to get rapid response. Sometimes they’ll bounce you around a lot to get you to the right person, but they are quite responsive (especially when you are paying for the service). Many of the older Microsoft skills are also transferable from old-school on-prem to Azure-based virtual interfaces.
As I have mentioned before the issue with my Oracle Mismatch Version issues that have put a delay on moving one of my platforms will justify my 7 rating.
Only IBM Watson Assistant has been the one we have used in the company, in fact, it was the first to use it because currently in the market there are not many options to use, and if there are they are not receiving enough publicity, so we have limited ourselves to google cloud contact center AI.
As I continue to evaluate the "big three" cloud providers for our clients, I make the following distinctions, though this gap continues to close. AWS is more granular, and inherently powerful in the configuration options compared to [Microsoft] Azure. It is a "developer" platform for cloud. However, Azure PowerShell is helping close this gap. Google Cloud is the leading containerization platform, largely thanks to it building kubernetes from the ground up. Azure containerization is getting better at having the same storage/deployment options.
