AI app for it and development · no coding needed
Source-linked code review and debugging console
Reduce review and debugging cycles while keeping a named engineer's approval on every change.
Made for: Engineering teams maintaining application codebases
What it does for you
The problem
Reviews, bug fixes and CI failures are handled in separate tools, so context is lost and fixes are not verified against the pipeline.
What it gives you
Engineer-approved fixes, review comments and tickets linked to source
What you give it
Repository codepull requestsCI logsissue-tracker tickets
Build your own version of Codara, AI Code Reviewer and more
One app with what these 10 AI tools do, yours to keep and change: Codara, AI Code Reviewer, Kodus, EntelligenceAI VSCode Extension, Codara Github AI Code Review App, Baz, CodeRabbit VSCode Extension, Gitar, Jam, Latta AI.
Everything these tools do, in one app
- Automated code analysis Scans code to find errors, issues, and potential improvements without manual review.Found in Codara, AI Code Reviewer, Kodus and 7 more
- Real-time suggestions Provides instant code suggestions and auto-completion as you write.Found in Codara, EntelligenceAI VSCode Extension, CodeRabbit VSCode Extension
- Multi-language support Works with multiple programming languages such as Python, JavaScript, and Java.Found in Codara, Kodus, Latta AI
- IDE integration Integrates directly into code editors like Visual Studio Code and IntelliJ IDEA.Found in Codara, EntelligenceAI VSCode Extension, CodeRabbit VSCode Extension
- Pull request review Automatically reviews code changes in pull requests and provides feedback.Found in Codara Github AI Code Review App, Kodus, Baz and 1 more
- Interactive Q&A Allows users to ask questions about the code for clarification and learning.Found in AI Code Reviewer
- Bug detection and fixing Identifies bugs and automatically applies fixes to resolve them.Found in Codara, EntelligenceAI VSCode Extension, CodeRabbit VSCode Extension and 3 more
- Code optimization Recommends improvements to enhance code performance and quality.Found in Codara, Baz
- CI failure diagnosis Diagnoses continuous integration failures and validates fixes against the pipeline.Found in Gitar
- Customizable workflow Adapts to team-specific coding standards and provides tailored feedback.Found in Kodus, EntelligenceAI VSCode Extension, CodeRabbit VSCode Extension
- Git integration Integrates with Git version control systems for seamless workflow.Found in Kodus, Baz, Gitar
- Bug reporting Automatically generates detailed bug reports with reproduction steps.Found in Jam
- Ticket automation Creates and pushes bug tickets directly to issue-tracking systems like Jira.Found in Jam
- Flaky test retries Automatically retries flaky tests to reduce false-positive CI failures.Found in Gitar
- Codebase context analysis Analyzes the entire codebase to provide comprehensive context for reviews.Found in EntelligenceAI VSCode Extension
- PR description generation Automatically generates meaningful pull request descriptions.Found in Baz
- Secure code review Reviews code for security vulnerabilities and coding standard compliance.Found in Jam
How it works, step by step
- Scan code for errors, issues and improvements
- Suggest fixes and completions while typing
- Support Python, JavaScript, Java and other languages
- Integrate with Visual Studio Code and IntelliJ IDEA
- Review pull request changes and post feedback
- Answer questions about the code
- Detect bugs and apply proposed fixes
- Recommend performance and quality improvements
- Diagnose CI failures and validate fixes against the pipeline
- Adapt to team coding standards
- Integrate with Git version control
- Generate bug reports with reproduction steps
- Create and push tickets to Jira and similar trackers
- Retry flaky tests to reduce false-positive CI failures
- Analyze the whole codebase for review context
- Generate pull request descriptions
- Review code for security vulnerabilities and standard compliance
- Compare the reviewed result with the recorded baseline and value assumptions
- Capture corrections and named-owner approval before merge
- Export a versioned engineer-approved fix, review comment or ticket with source references and unresolved questions
Build it yourself with your AI system
Build this app yourself, no coding needed
Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.
Sign in to see how to build it yourself
Build a quick version to try, or get the full app pack for Source-linked code review and debugging console with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.
4 Have it built for you days to a few weeks
Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Source-linked code review and debugging console with you.
What's in the app pack
Included in the Complete AI Training membership.
- The building instructions your AI follows, step by step
- The questions your AI will ask you about your business before it starts
- A clickable demo you can open in your browser, to see how it should work
- A detailed blueprint of the screens, the information it keeps and the checks it runs
Become a member to get the app packAlready a member? Sign in
The files, for the technically curious
- START-HERE.mdHow to build it with your own AI (read first)3 KB
- README.mdOverview and links5 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare25 KB
- prompt-vps.mdThe same build on your own server (Docker)25 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria13 KB
- demo/index.htmlThe working demo on sample data196 KB
Questions
Do I need to know how to code?
No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.
What does it cost?
The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.
How long does it take?
The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.
Can I change it to fit my business?
Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.
More detailsHow the AI works, safeguards and what to build first
Reduce review and debugging cycles while keeping a named engineer's approval on every change. For engineering teams maintaining application codebases, convert repository code, pull requests, CI logs and issue-tracker tickets into engineer-approved fixes, review comments and tickets linked to source. The benefit is a testable hypothesis, measured through accepted review comments per reviewer hour and corrections after merge; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect repository code, pull requests, CI logs and issue-tracker tickets, then follow this sequence: 1. Scan code for errors, issues and improvements. 2. Review pull request changes and post feedback. 3. Detect bugs and apply proposed fixes. 4. Diagnose CI failures and validate fixes against the pipeline. Resolve uncertain cases with qualified reviewers, approve engineer-approved fixes, review comments and tickets linked to source, and measure accepted review comments per reviewer hour and corrections after merge against a documented baseline.
How the AI works
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the three stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One repository host and one CI provider; final merge and security sign-off remain engineering. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve code authorship, source attribution, license accuracy and usage permissions. Engineers approve substantive changes and merge scope. One repository host and one CI provider; final merge and security sign-off remain engineering. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.
What to build first
Pilot scope: One repository host and one CI provider; final merge and security sign-off remain engineering. Implement one approved input format, a bounded representative case set and the first two task modules: scan code for errors, issues and improvements; review pull request changes and post feedback. Support the third module with operator review: detect bugs and apply proposed fixes. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.
What it can connect to
Developer-owned repositories, authorized CI logs and permitted issue-tracker tickets. Cloud code storage, Git host import/export and issue-tracker destinations. Start with file exchange and validate destination specifications before promising direct merge or ticket creation. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.
The screens in detail
Primary screens: Repository and review queue, Editable diff and fix preview, Client proof and delivery. Use a thumbnail gallery for repositories, a large central diff canvas, and a right-hand panel for source references, CI status and comments. Let users compare versions side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant line. Make the task-specific outcome engineer-approved fixes, review comments and tickets linked to source visible beside its evidence, review state and value baseline.
