AI Companion for Developers and SREs

AI that understands your code and debugs your production environment

Test Root Cause Analysis

CloudAEye’s Test RCA streamlines test failure diagnostics with AI-powered insights. Instantly pinpoint root causes across complex systems, simplify error analysis, and accelerate resolution—cutting down the time spent on debugging and getting your team back to building.

Test Failure Analysis

Automatically analyzes test failures, identifies root causes, and suggests fixes

Flaky Tests

Detect & fix flaky tests with CloudAEye’s Test RCA. Flaky tests pose significant risks by frequently producing false negatives or, even more critically, masking serious defects as false positives.

Triage Tests

Effective triaging prevents delays by quickly identifying test owners, assigning resolution tasks, and confirming fixes, ensuring issues don’t slip through the cracks. CloudAEye’s triaging feature streamlines this process, reducing manual effort and keeping your testing on track.

Code Review

CloudAEye’s Code Review integrates with your GitHub and simplifies your post-PR process. Get code reviews that highlight security vulnerabilities and bugs, complete PR descriptions with extensive reports on the changes included, and much more!

PR & Commit Descriptions

Add PR descriptions & commits and get detailed breakdown on the changes included in the PR with CloudAEye’s Code Review bot. CloudAEye can analyze and highlight potential bugs, vulnerabilities and errors in logic due to the changes involved.

Code Reviews

CloudAEye can review and highlight important bugs, and security vulnerabilities in your code in an instant! CloudAEye will also suggest the fix for the bugs and vulnerabilities detected which you can add to the PR with the click of a button. Fix your code - right from GitHub!

LLM Security

CloudAEye detects advanced vulnerabilities like indirect prompt injections, where hidden malicious inputs can manipulate AI models, exfiltrate data, or compromise system security. By uncovering these risks in your code and integrations, CloudAEye ensures your AI-driven workflows remain robust against emerging threats

AI Code Stability & Security

LLM-generated code can introduce risks like hardcoded secrets, logic errors, and unsafe dependencies. CloudAEye detects vulnerabilities and provides actionable fixes, ensuring your AI workflows are secure and reliable.

Why CloudAEye?

Self-Hosting of LLMs

CloudAEye can be deployed with a self-hosted LLM, ensuring enhanced data security and addressing any concerns.

Data Privacy

We support CloudAEye to be deployed in “on-prem” mode where all your data (ex. vector database) are hosted in your own account (ex. VPC).

Full Context

CloudAEye has comprehensive knowledge of your codebase and tests, potentially surpassing even your developers' understanding. This enables CloudAEye to deliver higher quality results and solve problems succinctly.

Improved Developer Productivity

Although coding is a developer's primary task, over 60% of their time is spent on activities like testing, deploying, bug fixing, and change management. CloudAEye boosts developer productivity by 15% to 20%, minimizing time lost to work environment obstacles. For a company with a $10 M engineering payroll, this translates to savings of $1.5 M to $2 M.

Zero Day Retention

We prioritize your data's security and confidentiality with zero day retention (ZDR) policy contracts with both OpenAI and Anthropic. Your code remains strictly confidential and is never used for model training. All data transmitted to the models is protected with TLS encryption to ensure security.

User Testimonials

“CloudAEye onboarding took only a few minutes. The AI services were great to identify operational issues and provided timely insights. We saved valuable time with the AIOps workflow”

Zakaria Swapan, Founder & CEO, Priyo

“I like how CloudAEye is using AI to enable faster recovery times in production. Easier on-call and happier SREs!”

Satish V, VP & Head of Engineering, AgriTech Startup

“CloudAEye's Kosal is the most novel approach of root causing incidents using AI that I have come across. This is a game changer and shapes up the next generation of incident management!”

Rajesh B., Sr. Staff Engineer, Enterprise FinTech Company

FAQs

What CI and test frameworks do you support?

We support GitHub, Jenkins, and an extensive list of test frameworks.

  • Python: PyTest, Testify, PyUnit
  • JavaScript: Jest, Cypress
  • Java: jUnit, TestNG
  • Go: Go Test, Testify
  • Kotlin: Kotest, jUnit + Strikt
  • Frameworks with support for many languages.
  • Playwright: TypeScript, JavaScript, Python, .NET, Java
  • Selenium: Java, Python, C#, and Ruby
  • TestCafe: JavaScript, TypeScript, and C#
  • Robot Framework: Python, Java, and .NET (C#, IronPython)
  • Cucumber: Java, JavaScript, .Net
  • Can CloudAEye be deployed where all my data is stored securely in my own account?

    We offer Deploy "In your VPC" mode where all your data is hosted in your own VPC. Additionally, CloudAEye provides several options for running LLMs, tailored to meet your specific needs:
  • Dedicated LLM: Hosted in AWS or through an external GPU provider.
  • Amazon Bedrock Model: Utilize a model from Amazon's Bedrock service.
  • Bring Your Own LLM: Supply your own LLM key and provider details, and we'll integrate it into our platform.
  • Is Test Root Cause Analysis free?

    Yes! The individual developer plan for Test Root Cause Analysis is free. For team or enterprise needs, we offer paid plans. For more details, please visit our pricing page.

    What programming languages does CloudAEye support?

    CloudAEye supports all programming languages, with high-quality responses prioritized for Python, JavaScript, TypeScript, Java, Go, C#, C++, C, and Kotlin.

    Can I request to delete any stored data?

    Yes. You may configure a retention policy for all your data.

    Who owns the copyright to the generated code & suggestions?

    You have the sole copyright and ownership over the generated code and suggestions from CloudAEye's services.