OpenVino logo

OpenVINO Pro for Enterprise

OpenVino logo
OpenVino logo

OpenVINO Pro for Enterprise

By Intel Corporation

Certified enterprise ready

Accelerate development of high-performance computer vision and deep learning inference on Intel® technology-based platforms. OpenVINO™ Pro for Enterprise offers support, added services, and exclusive access to future code releases.

Software version

2021.4

Runs on

OpenShift 4.2+

Delivery method

Operator

OpenVINO™ Pro for Enterprise is a complete toolkit for developing AI on Intel® hardware, with proactive enterprise services, business-class support, and exclusive code releases. This professional toolkit optimizes and converts deep learning models into high-performance inference engines that can scale automatically to thousands of nodes with Red Hat OpenShift. Improve performance and availability at low cost and help meet security and compliance requirements while accelerating time to value.

OpenVINO Model Server - High Availability & Enterprise Scale

Model Server detects new model versions added to the remote or local model repository and monitors configuration changes. All updates in served models are applied in runtime without interrupting the service. This allows hot swapping of new models into production or updating versions of existing models. Server models are trained in popular formats such as Caffe, TensorFlow, MXNet and PyTorch/ONNX. Server directly models in OpenVINO Intermediate Representation or ONNX format.

Enterprise Lifecycle Services - Accelerate Business Outcomes

Address the evolving needs of your complex business and technology environment with services for the lifecycle of your AI applications, from pre-deployment planning to building and operations. Accelerate your innovation using expertise from Intel and our Partners for the entire solution lifecycle including, solution definition, detailed design, application development, deployment, ongoing maintenance, and ongoing improvements.

Software Updates and Enterprise-class Support

Get access to Intel’s 24x7 multi-channel technical support to ensure high availability of your applications. Production releases are supported with bug-fixes, security, and compatibility updates for 3-years from first release.

Pricing summary

Plans starting at

View all pricing options

Access to all product features and functionalities

Access to Intel’s direct enterprise services during the free trial

Free trial for up to 90 days with no lock-in or commitment

Additional resources

Want more product information? Explore detailed information about using this product and where to find additional help.

Reviews

Read what others are saying about this product in our review section.

Showing 1-5 of 13

  • AS

    Administrator in Information Technology and Services

    Verified Current User
    Review source: Invitation from G2
    Verified Current User
    Review source: Invitation from G2
    Not ratedSep 27, 2021

    "Real time CPU inference"

    What do you like best?

    The most important upside of OpenVino is ability to predict real time on CPU. It also has various accelerators like GPU, VPU, FPGA. OpenVino's documentation is very well maintained. Hence, its easy to use. We can also customize OpenCL. We can also prune and quantize deep learning models. It has its own benchmarking tool. It has many model conversion features. Like converting any model to its intermediate representation from onnx,pytorch,tensorflow, keras. It has many sample Deep learning/computer vision examples that are already well optimized.

    What do you dislike?

    It has many versions. So you need to stay updated in our to run various DL models efficiently. You might get version conflicts. Its feature of model optimization is a bit slow. It becomes difficult to convert latest state of the art models due to internal layer implementation. Training complex neural network can be a concern as model conversion can be quite typical. Also it does not have more references for beginners. These are the things I do not like about Openvino and needs improvements.

    Recommendations to others considering the product:

    I would totally recommend OpenVino to all the users in the field of Computer Vision and Deep learning. From my personal experience, it is very simple to setup. Has great documentation and community support. You will be able to achieve higher FPS with great accuracy. And when thinking about scalability of a usecase on a CPU, OpenVino will be the best choice. Even for edge deployments, its has many accelerators. Hence anyone looking for wdge deployments as well. It is a great choice for smaller light weight models.

    What problems are you solving with the product? What benefits have you realized?

    Well I have been using Openvino for various computer vision applications. All the LPU deployments that are CPU based and needs higher processing speed with accuracy are done using OpenVino. It has also been helpful in converting heavy complex model to light weight faster simpler model. Its serving architecture is a great feature for handling multiple streams all at once. Hence, openvino benifits us in terms of scalability, throughput and accuracy.

  • saurabh p.

    saurabh p.

    Creative Programmer at IT souls

    Review source: Invitation from G2
    Review source: Invitation from G2
    Not ratedSep 25, 2021

    "It was fun and amazing experience to use and learn OpenVino."

    What do you like best?

    I majorly like that OpenVino available for most of the platforms, which is one of my top features. Apart from this, the workflow and the documentation of how to use it are unique too. I majorly like that OpenVino available for most of the platforms, which is one of my top features. Apart from this, the workflow and the documentation of how to use it are unique too. I advise those who are seeking to learn something latest up-to-the-date toolkit I must suggest using this and as per my experience, they will know and built a lot of new things.

    What do you dislike?

    When I was commencing this, I found little difficulty, but after some time, I understood all very well.

    Recommendations to others considering the product:

    I advise those who are seeking to learn something latest up-to-the-date toolkit I must suggest using this and as per my experience, they will know and built a lot of new things. I advise those who are seeking to learn something latest up-to-the-date toolkit I must suggest using this and as per my experience, they will know and built a lot of new things.

    What problems are you solving with the product? What benefits have you realized?

    I solved many of OpenCV and helped to solve some Augmented Reality and other issues which I was facing previously. Also, it's easy to use and learn, so it's very beneficial for me. I advise those who are seeking to learn something latest up-to-the-date toolkit I must suggest using this and as per my experience, they will know and built a lot of new things.

  • UC

    User in Hospital & Health Care

    Review source: Invitation from G2
    Review source: Invitation from G2
    Not ratedSep 22, 2021

    "Openvino is one of the most industry ready inference engine available now"

    What do you like best?

    OpenVino has a lot of resources and examples, which can be utilized to build our own custom deep learning solutions. OpenVino has worked very well in industrial projects, especially in custom computer vision solutions. Also, it is very easy to integrate with Python projects and can run on a plethora of devices, which makes it an ideal choice as an inference engine.

    What do you dislike?

    The learning curve is a bit steep for beginner and novice developers.

    Recommendations to others considering the product:

    Having an intermediate knowledge of deep learning will help a lot to build faster with OpenVino.

    What problems are you solving with the product? What benefits have you realized?

    We are creating computer vision solutions for detecting watermarks, identifying custom logos from images, text retrieval from images, etc. The existing resources helped us a lot in getting a head start. The development pipeline is smooth and the inferencing is a lot faster compared to other similar solutions.

  • Shoaib A.

    Shoaib A.

    Serving Notice Period. Working on AI,Maths, Python, Devops, Automation, Git, OpenVINO

    Review source: Invitation from G2
    Review source: Invitation from G2
    Not ratedSep 24, 2021

    "First hand review as a Developer/User."

    What do you like best?

    Deep Learning models support, IR Format, Model Optimization, Ngraph Bridge, etc. The list goes on...

    What do you dislike?

    Some Models failed by model optimizers to convert IR Files. And the conversion should be both ways optimized and not optimized; sometimes, I want to retain my ops and nodes.

    Recommendations to others considering the product:

    It's basically a ready set go process, if you work on Deep Learning Models, OpenVINO is the Best Tool for it, be it inferencing, optimizations, or anything

    What problems are you solving with the product? What benefits have you realized?

    Generally Model Optimizations, And I love its Inference Engine as well.

  • marcia かおる w.

    marcia かおる w.

    Chief Guru

    Review source: Invitation from G2
    Review source: Invitation from G2
    Not ratedSep 26, 2021

    "Machine learning mechanic"

    What do you like best?

    I like the pre-trained models. I like the ease of setting up and getting started.

    What do you dislike?

    With each iteration they change things and the file structure or hierarchy so certain things needed to be changed. Also with different iterations there was a need to change plugins.

    What problems are you solving with the product? What benefits have you realized?

    I enjoy the benefit of using object and different types of recognition systems cleanly out of the box without having to train models myself but being able to use image net and other networks.