GitHub Copilot is presented as an AI pair programmer, that plugs into the user's editor. It then turns natural language prompts into code, offers multi-line function suggestions, speeds up test generation, filters out common vulnerable coding patterns, and blocks suggestions matching public code.
$10
per month
IBM watsonx Orchestrate
Score 8.7 out of 10
N/A
IBM® watsonx™ Orchestrate® leverages AI to automate complex workflows. The solution helps build, deploy, and manage AI assistants and agents. It offers a catalogue of pre-built agents and tools, low-code agent builder, multi-agent collaboration capabilities, and integrations with enterprise apps.
$500
per month per subscription
Pricing
GitHub Copilot
IBM watsonx Orchestrate
Editions & Modules
CoPilot for Individuals
$10
per month
CoPilot for Business
$19
per month per user
Essential
$500
per month per subscription
Essentials
$500
per month Per subscription
Standard
Enterprise
Standard
Enterprise
per month Per subscription
Offerings
Pricing Offerings
GitHub Copilot
IBM watsonx Orchestrate
Free Trial
Yes
Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
Optional
Additional Details
—
IBM watsonx Orchestrate can be deployed and run on IBM Cloud, AWS, or on-premises. Prices shown are indicative, may vary by country, exclude any applicable taxes and duties, and are subject to product offering availability in a locale.
More Pricing Information
Community Pulse
GitHub Copilot
IBM watsonx Orchestrate
Considered Both Products
GitHub Copilot
Verified User
Anonymous
Chose GitHub Copilot
In terms of AI and developing tasks, GitHub Copilot is the only tool I have used so far. Copilot Work, Copilot Web, Copilot Teams, Copilot Excel, Copilot Word, Copilot Outlook, Copilot Power Point are other agents of Copilot that I use daily, but are all complementary of GitHub …
ChatGPT, Perplexity, and Grok are AI tools that developers use to boost productivity. However, GitHub Copilot outperforms them due to its tight integration with Visual Studio. GitHub Copilot can analyze all the code in your workspace and provide contextual assistance within …
It has historically worked much better. However, as all of this is relatively new technology it is hard to really judge something since most of the time you are kind of using a beta version of a product. I believe things will get better over time. That said, Microsoft copilot …
It is useful that copilot integrates so well with vscode, which is a very common IDE. I used tabnine for a little while but it was not that intuitive, and did not seem as helpful as github copilot was. I have enjoyed github copilot a lot, especially the ease of hitting the tab …
I have also used Anthropic's Claude code Its amazing, and I would say it is even better than GitHub Copilot. However, the only issue with claude code is its subscription price, which is very very high as compared to GitHub Copilot.
I used cursor AI as well, along with CoPilot. Curson has its own AI editor, but Copilot works with almost every code editor. So I don't need to depend on just one editor, and I get the flexibility to choose my own editors. The billing is also good and doesn't require many …
I think this product's got a lot more use cases from a business standpoint. I find the other products are very based in end users and also the orchestrator has a lot more agnostic connections to a lot of products, whereas Microsoft is very Microsoft dominated and the other …
The other solution provides far more capabilities but at a much higher price and far more complexity. The IBM watsonx Orchestrate tool is less expensive (about 25% of the other solution) while being good enough for what we needed and being easy to use.
Strong ITSM and HR workflow automation with governance, ServiceNow excels in IT/HR but lacks flexibility for cross-departmental use cases such as demand planning, finance close, or procurement analytics. Orchestrate supports a broader set of enterprise functions beyond IT …
Google Cloud Dialogflow, Amazon Lex, and Azure AI Bot Service were assessed before selecting IBM watsonx Assistant. The primary reason we used IBM watsonx Assistant is the ability to remember diverse contexts during the multiphase bookings and to support multiple languages that …
The code generation feature of IBM watsonx Assistant was slightly better than in ChatGPT and Vertex AI. However that might change in the future since AI engines are evolving very quickly.
Similar positions for similar purposes include Google Cloud DialogFlow and Azure AI Bot Service that I have considered. As opposed to Dialogflow, IBM watsonx Assistant is more tightly linked to comprehensive analytical units that provide clearer and more comprehensive data …
My experience working with Microsoft Bot Framework and Dialogflow has shown that Watson Assistant features an intuitive interface combined with powerful analytics. We selected Watson Assistant because it strikes an excellent balance between providing powerful capabilities while …
Make has more community of workflows to follow that have been redeveloped and are available for download. Selecting WxO is based on our trust level with IBM and the propositions of the Granite model being less biased, more business trained, and the ecosystem allowing for …
I selected IBM watsonx Assistant so I could maintain the NLP/NLU processing from our last supplier (which was not Twilio). Since we switched, I have not liked IBM watsonx Assistant so much. We are sincerely thinking about changing it to a new one, the Kore.AI which seems easier …
Copilit is fantastic at the following: 1. Solving simple, well-defined problems, such as implementing an algorithm, manipulating a data structure, or string manipulation and regex. 2. Implementing simple APIs that are mainly CRUD in nature, with moderate business logic inside them, which may involve some processing or passing the data through an algorithm. 3. Implementation of well-defined activities, such as implementing a connection to an Oracle DB using Hibernate or JDBC, or implementing boilerplate code for a backend service to listen to Kafka events. It is not that great when it comes to understanding and implementing code in a proprietary DSL. It struggles when implementing a major feature across a complex codebase. I believe developers should also adopt the trust-but-verify paradigm when expecting highly secure or regulated code from GitHub Copilot.
In our case, it is well-suited for workday integration, which allows us to automate the entire workflow. However, we are still working on the O9 platform integration, which we feel is less appropriate, and integrating the workflow into the platform.
IBM Watson simply works well for my organisation. We were able to design, build, and deploy a fully integrated chatbot in a matter of months. The basic building blocks (intents, skills, dialogue nodes, integration) are relatively straightforward for a technical developer to work with. The bot now supports retail customers in 3 different countries on both web and app based channels. We plan to further develop the bot to expand the way it interacts with customers through voice to text, and optical character recognition, as well as an improved UI.
I feel that GitHub Copilot's overall usability is good due to its tight integration with Visual Studio and the workspace. However, developers expect greater ease of use, as there is a learning curve to realize productivity gains with the tool fully. I think there is room for improvement in GitHub Copilot's UI integration within Visual Studio.
With the growing use of AI and chatbots, it's very easy to use, and the conversational language makes it easier than keyword searches in a document. The contextual language processing is impressive. It's easy to integrate into our internal portal. The use of this tool would depend on each company's security and data sensitivity.
To develop chatbots based on client provided flow what kind chatbot required for client either button or free text chatbots. we will decided accordingly flow and develop chatbot using IBM Watson. We will integrated custom components if required which is not present in library. IBM Watson library anyone can easily learn and develop chatbots.
We've rarely had to engage support, but they've always been prompt in responding and very attentive. Support experiences have been extremely positive (but we're mostly happy that we just don't have any cause to routinely need support in the first place!).
I used Cursor AI as well, along with CoPilot. Curson has its own AI editor, but Copilot works with almost every code editor. So I don't need to depend on just one editor, and I get the flexibility to choose my own editors. The billing is also good and doesn't require many coupons to write prompts.
I think this product's got a lot more use cases from a business standpoint. I find the other products are very based in end users and also the orchestrator has a lot more agnostic connections to a lot of products, whereas Microsoft is very Microsoft dominated and the other products are very technical and not business focused.
From past 3+ years I am using IBM Watson in our current project easily can implement and manage and monitor user how their using. Is there and update also just update dialog is just enough to change no need to touch any other templates. Multiple language will support, and action and dialog speak recognize chatbot we can create as per client requirement. Overall, as of now good experience with IBM Watson.
The clients have received additional, rather enhanced, individual conversion rates of users who interact with the virtual assistant.
Due to the introduction of automated methods of handling a majority of the calls that are made, many call center agents are thus left to handle only complicated cases.
According to a more advanced understanding of patterns, the assistant has been critical in suggesting solutions and thus drove optional revenue management.