A platform for developing generative AI solutions and custom copilots. Azure AI Studio includes catalog of models from OpenAI, Hugging Face, and Meta, that can be applied over in-house data. It is intended for professional software developers—including cloud architects and technical decision-makers—who want to create generative AI applications and custom copilot experiences.
N/A
InRule
Score10 out of 10
N/A
InRule Technology in Chicago, Illinois offers business rules management software.
I am deploying a lot of pipelines and making a lot of variants of these pipeline segments, like different types of vector search techniques. The simple way to mix and fix these segments to run the whole pipelines in notebooks options are big overhead killer. The playground which provides a test sandbox helps a lot to evaluate LMs if they are the best fit for our use-case even before deploying and startup with the costing angle.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
With InRule, we are expecting to be able to move business logic out of the developer domain and back into the business domain. Business logic is currently captured in UI (data validation) and middleware layers. These are areas in any application where leveraging InRule's capabilities allow for changes in business logic to be made with little or no IT involvement.
Wide Catalog of Models is a beautiful feature for all who want to evaluate a lot of models before proceeding with any client use case for the best performance.
Playground for testing and evaluating visual comparisons on so many metrics like latency, cost, and output time.
Integration with other Cloud services, this makes the full complete solutioning and vision complete, from storage to compute.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Model Catalog can have a feature to show basic compute and the cost of running the model on that compute. With latency metrics, I generally need to do a lot of research before losing some dollars on deployment on hit and trials.
Documentation generator for pipelines deployed in notebooks, generally developers use notebooks for experimentation, where logging them can be a big overhead.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Microsoft Foundry includes the existing AI Services. It's quite literally Cognitive Services under the hood, so in that sense, if you're building a new "AI app" today where you would have deployed an AI Services Account, you can deploy Microsoft Foundry instead. The side benefit of that is that Foundry also includes model deployments, and more than just the OpenAI models. So, it removes the need for deploying a separate Azure OpenAI Service in some circumstances. Then finally it has agent capabilities too. So, if you're developing and deploying agents as part of your solution (which usually interface with a model) then you can do that from there as well. Effectively it's meant to be a one-stop-shop for all things AI, just like Fabric is for data.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
InRule's Support Portal provides a "one stop shop" for submitting support questions, accessing training information, managing licenses, and getting updates on InRule's roadmap.
Azure AI Studio were the pioneers of DevOPs, so MLOPs feels quite a bit better on this platform than Google. Azure brought OpenAI into the system which made the Organization to shift from any other platform to Azure AI Studio.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
InRule offers a more organized software design, a well-structured framework in design, and is easier for new users to start contributing given documentation. Drools is spreadsheet-based and lacking the capability to do really advanced pseudo-programming.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Onboarding a team member for the codebase is slightly slower, almost 20% slower. As codebase sharing is like a git pull from repos, whereas here we need to provide all the access.
I have experienced scaling up speed almost 50% faster as per compared with on-prem solutions. ML models are faster deployed in terms of on-prem deployments.
10 times better Azure AI Studio for cost visibility over any other solution.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info