GitHub Copilot vs. Jeeva AI

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.

Incentivized

Independently Invited by TrustRadius

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

If anyone is looking to pile up the list of email lists to send out e-blast or cold messages, I would highly recommend Jeeva AI. However, if anyone needs more of organic work, I would recommend using Jeeva AI to collect contact information, but do the work manually.

• Make code development faster and quicker.
• Helps write better code standards for projects.
• Provide the latest functions from the technology.
• Notifies about the deprecated functions.

Incentivized

Independently Invited by TrustRadius

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

• Finding specific leads according to descriptions provided
• Allowing customers to experience Jeeva AI by offering free credits
• Following up with leads

• The only issue I faced is the context token size, it can be increase.
• Sometime with agent mode it takes too much time, which can be reduced but I understand it also depends on the complexity of the given task.

Incentivized

Independently Invited by TrustRadius

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

• You run out of credits very fast, they charge per email sent. The credits should be for lead generation not emailing.
• Incorporate delivery results, bounce results, mailer unfound results, etc... We can not see any of those metrics.
• Incorporate a text sequence campaign as well. To be one stop shop for contacting all ways.

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.

Incentivized

Independently Invited by TrustRadius

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

Jeeva is composed of individual products / features that form a robust, automation-based, outbound system when combined. Parts of the tech stack within Jeeva itself – can be difficult to work with independently. Some of what the individual products provided makes you ask why? Why was this individual product / feature implemented

Incentivized

Independently Invited by TrustRadius

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

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 key and seeing quick progress in my tasks.

Incentivized

Independently Invited by TrustRadius

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

Jeeva AI is less straightforward than Sales Nav. It seems that it is trying to be everything that Sales Nav is, but not quite achieving it yet. The customer service for Linkedin is far superior to Jeeva's. Jeeva's team refused to give me a refund on my first month's subscription despite their refund policy clearly stating that I was entitled to it. This has never happened before with Linkedin Sales Nav.

Incentivized

Independently Invited by TrustRadius

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

• Our ROI of the purchase of Copilot was met in less than a day. The timesave cannot be overstated
• Programmer boredom/dissatisfaction is down because of less repetetive crud work.

Incentivized

Independently Invited by TrustRadius

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

• We just started and was great for lead generation
• Those leads we can manually email them or call them
• Our sequence campaigns are barely 1 email in, looking forward to see if we get any traction on the last 2 sequences