Covlant is an AI company focused on enhancing developer productivity by helping software engineering teams produce higher-quality code at an accelerated pace. Compatible with multiple programming languages like Python, Java, Scala, Golang.  Covlant integrates seamlessly with popular development tools like GitHub and Bitbucket. The company’s exclusive Covlant Neural Engine offers advanced code intelligence, while the Covlant Cloud Build System enables developers to work faster by delivering consistently runnable, high-coverage, and meaningful tests within their development environment. 

Covlant revolutionizes software development by enhancing developer productivity and minimizing downtime. Our solutions empower developers to identify bugs early, deliver high-quality products, and speed up time-to-market. With AI-driven quality assurance, we help businesses achieve success and gain a competitive advantage. 

Quality issues can significantly influence the success of a business. While test cases are crucial, they are frequently perceived as tedious tasks. Developers, often swamped with responsibilities, may resort to writing placeholder tests that fail to fulfill their intended purpose. As a result, quality assurance can devolve into a mere box-ticking exercise. 

We believe there is a more effective way to address these challenges. Drawing from our extensive industry experience, we understand these obstacles intimately. Our passion lies in harnessing AI to transform quality assurance into a more effective and engaging process for developers. 

Few would dispute that Generative AI (GenAI) is set to revolutionize code development. By automating repetitive tasks, boosting collaboration, and speeding up the coding process, GenAI enables developers to focus more on complex problem-solving and the creative aspects of their work.

Covlant recognizes that this shift will take time, as it represents a transformational change in how code has been developed for decades. One area we believe has been largely overlooked is test code generation. Research consistently shows that higher test coverage results in higher-quality code with fewer defects. Additionally, developers often dislike writing test code and are open to exploring GenAI solutions to assist, as developer surveys indicate.

One challenge with GenAI-generated code is that it isn’t always executable. Covlant believes that its Neural Engine and Build System have overcome the inherent issues often encountered when using GenAI to write code—particularly test code in Covlant’s case.

Deep Code Analysis: Covlant analyzes the codebase with a comprehensive understanding of the source code’s functionality, featuring a CLI chatbot that allows developers to ask questions and gain actionable insights. 

Custom Test Code Generation: Developers initiate test code creation, tailored to the specific file or set of files they are working on. 

Utilization of Public LLMs: Rather than training or fine-tuning its own large language models (LLMs), Covlant leverages publicly available models such as OpenAI, Anthropic, and Llama. 

Flexible Deployment Options: The Neural Engine and Build System can be deployed in Covlant’s cloud, on-premises in customer data centers, or within existing cloud environments. 

● Supported LLMs: OpenAI, Azure OpenAI, Anthropic, Llama
● Languages Supported: Java, Python, Golang, Scala
● Deployment models: On-premises or SaaS
● API Availability: Present, not currently released as of Nov. 2024

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