We are proud to be recognized by Gartner in the inaugural 2024 Gartner Magic Quadrant™ and Gartner Critical Capabilities for AI Code Assistants. Codeium is named a Challenger in the Magic Quadrant, is ranked amongst the three highest scoring vendors for all 5 Use Cases in the Critical Capabilities report (out of 12 vendors evaluated), and ranked highest for both the Code Modernization Use Case and the Artifact Building & Testing Use Case. We believe this position acknowledges our execution to drive real value with AI Code Assistants for enterprises today, even in the most complex tech stacks and environments.

About Codeium

Codeium is an AI code assistant that helps accelerate time to delivery of products & services by helping with code generation, debugging, testing, modernization, and more. Codeium’s advanced context awareness capabilities and organizational guidelines help companies maximize their competitive advantage through technological excellence. Through its variety of deployment options, including air-gapped environments, and other enterprise readiness capabilities, Codeium can minimize operational risk in your AI strategy.

In the Gartner Critical Capabilities for AI Code Assistants, Codeium was ranked (out of 12 vendors evaluated):

1st for Code Modernization Use Case
1st for Artifact Building & Testing Use Case
2nd for Code Generation Use Case
2nd for Code Debugging Use Case
3rd for Code Explanation Use Case

How Codeium Can Help Your Organization

Codeium has been adopted by enterprises of all sizes and industries as the AI assistant of choice for their developers, including Dell Technologies, Zillow, and Anduril.

Now supporting over a thousand enterprises, we have deeply learned organizational pain points and have delivered solutions that address these directly. Here’s what we have found, and what we have delivered.

Accelerate Time to Delivery

Technical leaders are constantly looking to speed up delivery of products & services to bring them to market more quickly, achieving OKRs & increasing revenue, but are unable to today because of:

Slow/prolonged development cycles: Projects & initiatives are constantly delivered behind schedule, and there is a large backlog of tasks, ideas, and products
Active developers cannot be efficient: Whether it is a complicated tech stack, poor documentation, incomplete testing, inefficient engineering processes, and disjointed cross-team collaboration, developers are not able to do their best work.
Struggle to onboard newly hired developers and/or onboard developers onto different projects: Similar reasons to the previous, but the inflexibility to move resources around because of the difficulty to reason about newly seen code makes it harder to run a lean team. The struggle to onboard also saps time from senior engineers who spend too much time assisting with training & onboarding, or from internal engineers trying to ramp on and internally integrate contractor-written code.

With code suggestions, IDE-integrated chat, and inline refactoring capabilities, Codeium has a wide set of functionalities, available on the largest set of IDEs (including Visual Studio Code, JetBrains, Visual Studio, Eclipse, XCode, Jupyter, Vim/Neovim, and more) and supporting the most programming languages (over 70). Codeium provides detailed analytics dashboards for each organization to track the immediate impact of Codeium to their software development.

On average, developers using Codeium generate 44.6% of their newly committed code with Codeium (based on actual performance data from Codeium’s 700K+ users), leading to a 20-25% decrease in pull request cycle times.

Maximize Technological Excellence

Technical leaders are looking at setting the foundations for long-term success by establishing standards, reducing tech debt, accelerating modernization, and retaining talent. This would allow them to deliver on strategic initiatives faster, better, and bigger than before, yet face a number of challenges in these efforts as well:

Accumulated technical debt slows down the development process and reduces performance: Whether it is buggy code, code that doesn’t conform to company guidelines, code sprawl and duplicated logic, deprecated code, or disparate application of standards and “best practices”, it is challenging to tackle tech debt today, leading to high amounts of time and resources spent triaging issues than writing new code, and a general slowdown in work.
Long outstanding backlog for modernization: Legacy systems and outdated technologies hinder innovation and scalability, but framework upgrades/migrations, language migrations, and infrastructure upgrades all take a large amount of effort with no direct impact to business outcomes.
Poor technology culture: It is hard to lay the foundation for long-term success if there is poor adoption of coding practices, poor code review culture, and a siloed understanding of the tech stack. Related, not adopting the latest desired developer tools or not getting adoption & usage keep a technical team stagnant.
Inability to attract, onboard, and retain leading developer talent, preventing the organization from achieving initiatives: At the end of the day, the people on the team determine the potential of long term success, but it is hard to attract talent if the company is perceived to be behind or backwards on technology, hard to onboard talent for the onboarding reasons mentioned earlier, and hard to to retain talent if there is low employee satisfaction of the work they are doing and how they are asked to do it.

Codeium is able to set your technical organization up for scale by establishing standards, reducing tech debt, and accelerating modernization through its context awareness system that can reason over entire (and even multiple) repositories, as well as custom organizational guidelines to encode best practices of your particular software development. By providing organizations with context-aware AI, Codeium customers have observed 4x faster onboarding times and happier workforces, allowing them to retain talent and deliver on strategic initiatives faster, better, and bigger than they were able to do before.

Minimize Risk in AI Strategy

While AI promises to help address a lot of the above issues, technical leaders are well aware of the risks that are associated with adopting AI, and are looking to mitigate their risk in their AI strategy by ensuring security & compliance measures, fostering adoption, effectively managing change, and avoiding vendor lock-in. Some of the concerns around AI include:

Organization has been unable to adopt AI at scale due to security & compliance concerns: Whether it is a fear that AI systems are prone to security breaches and data leaks, lack of robust security measures in these tools (eg. RBAC) exposes sensitive data to unauthorized parties, failing to meet industry-specific compliance requirements or exposing to regulatory penalties, there are a long list of concerns. The most common with regards to code include not wanting code IP being stored in third-party locations out of their control, a fear that third party AI services train general systems on private code IP, and a possibility of incorporating non-permissively licensed code or other unusable code by accident.
Organization tries adopting AI with little to no success: In such a fast space, leaders are worried about choosing an AI tool that does not move as fast as the industry or incorporate most recent breakthroughs, or bringing on AI tools but not having any change management plans to enable/train employees to use of them effectively (which leads to low adoption). Similarly, it may be difficult to track how AI results are being incorporated into the codebase or have minimal visibility into the value that AI tools are providing.
Organization wants to avoid vendor lock-in: There is worry that achieving full feature functionality of a vendor’s AI tools requires full adoption of the vendor specific stack, and dependence on a single AI vendor limits flexibility and increases risks.

Codeium does not want its enterprise customers to compromise on their enterprise standards, and helps mitigate operational risk in AI strategy by ensuring security & compliance measures, SOC2 Type 2 compliance, no training on user code or non-permissively licensed code, providing attribution & audit logging, first-party RBAC support, and more. Codeium provides white glove service in change management and AI adoption, all while never forcing vendor lock-in to other parts of the customer’s tech stack. With Codeium’s first-principles approach to enterprise requirements, Codeium has successfully scaled private deployments to tens of thousands of developers within individual, regulated Fortune 500 organizations.

Continuing to Execute

Codeium is singularly focused on providing the best AI assistance to enterprise software development teams. In the last couple of months alone, Codeium has rolled out:

Riptide: a new paradigm towards reasoning that outperforms previously state-of-the-art approaches, covered by Forbes and others
Forge: an AI assistant for the code review process
Hybrid: a novel deployment method that combines the benefits of cloud and self-hosted deployments
Better Chat than ChatGPT: a long list of improvements across the model, reasoning, and UX layers to dramatically improve the in-IDE chat experience

With a singular mission to allow every developer to dream bigger and do work larger, better, and faster than before, Codeium will continue to execute and drive value today to its users and customers.

Disclaimer

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and/or its affiliates and are used herein with permission. All rights reserved.

Gartner, Magic Quadrant for AI Code Assistants, 19 August 2024, Arun Batchu, Philip Walsh, Matt Brasier, Haritha Khandabattu

Gartner, Critical Capabilities for AI Code Assistants, 19 August 2024, Arun Batchu, Philip Walsh, Matt Brasier, Haritha Khandabattu