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 8.8 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.
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.