industry

Introducing the Windsurf Editor, our new IDE.

Minimizing developer onboarding time is critical for any serious enterprise.

Announcing our induction into the JPMorganChase Hall of Innovation.

Why should we care about analytics? What could go wrong?

Codeium is named a Challenger in the Magic Quadrant.

Our model strategy is simple. Whatever delivers the most value.

Announcing Codeium on VMware Private AI by Broadcom.

An analysis and test of the AI code assistant tool from Google.

We break down the value of context awareness and finetuning to personalize the Codeium system to particular enterprises.

A feature-by-feature analysis of the new GitHub Copilot tier.

Breaking down the reasons why on-premise ends up being the more cost-effective method of deployment for generative AI applications.

Announcing our partnership and work with Dell.

Announcing our integrations and work with Atlassian.

How latency constraints enable us to use our infrastructure expertise to make better products.

Announcing our integration and partnership with MongoDB. Get started with MongoDB and Codeium in under 5 minutes using this tutorial.

We introduce two metrics, Characters per Opportunity (CPO) and Percentage Code Written (PCW), which we believe should be the gold standards for benchmarking AI code assistants and assessing end value driven, respectively.

A mental model of how we think about maximizing the value of AI tools.

Our takes on an eventful ending to 2023.

Announcing our first class integration and partnership with CodeSandbox.

We tested the claim that LLMs can catch security vulnerabilities.

Demystifying common misconceptions about the difficulties in running Codeium in a self-hosted manner.

Clarifying the GitHub Copilot for Business offering.

Why it is hard to create a context reasoning engine for code LLMs that consistently works.

A deep dive into context awareness of Codeium and how it stacks up against GitHub Copilot and CopilotX.

Why real-time context for AI code assistants is a meaningful and tricky problem.

An analysis on the capabilities and performance of the AI code assistant from GitLab.

Design great AI Products that go beyond "just LLM Wrappers": make AI more present, more practical, and more powerful.

Proof that Codeium fine-tuned on a repository significantly outperforms GitHub Copilot.

Codeium for Enterprises is purpose built to run on-prem or in your VPC - no data or telemetry ever leaves.

How Visual Studio Code does not have an even playing field when it comes to AI tooling.

In-line Fill-in-the-Middle suggestions, valuable suggestions produced only by Codeium.

Generative AI poses risks for companies that do not have strict data governance

An in-depth analysis on the capabilities and performance of Amazon CodeWhisperer post-general access release.

Demonstrating that GitHub Copilot trains on non-permissive licenses and is unable to filter out suggestions properly, while Codeium does not expose users to legal risk.

More security incidents, this time with ChatGPT, further support self-hosted solutions.

How tuning the model layer of LLM applications creates the highest quality experiences for enterprises.

Analyzing how fill-in-the-middle allows Codeium to make better suggestions.

Looking into the likelihood of security incidents and how self-hosting is the solution.

The theory, challenges, and future of code syntax parsing.

An aggregation of the best AI product aggregators for discovery.

The first head to head assessment of the leading AI powered code assistants: Github Copilot, Tabnine, Replit Ghostwriter, and Codeium.

How a user study and the rise of ChatGPT point to the underlying product issue of Github Copilot.

A "Copilot for X" guide from the team that built the first real Copilot competitor!