Konveyor AI (Kai) - AI Developer Tools Tool

Overview

Konveyor AI (Kai) is an open-source, model-agnostic tool that applies Retrieval-Augmented Generation (RAG) to speed and scale application modernization. Kai uses Konveyor static-code analysis (Kantra/analyzer-lsp) and a history of previously “solved” migration examples to build context-aware prompts for any LLM you choose, returning targeted code-change suggestions, reasoning, and optional automatic edits surfaced in the developer IDE. The project focuses on migration-focused transformations (for example Java EE → Quarkus, Spring Boot upgrades, or containerization patterns) and intentionally avoids one-size-fits-all generation by constraining outputs to issues discovered by static analysis and organization-specific solved-examples. ([github.com](https://github.com/konveyor/kai)) Kai’s workflow is developer-centric: analysis issues are discovered via Konveyor analyzer, Kai finds organization-specific solved examples, it augments requests with relevant analysis context and examples, and an LLM returns a suggested fix that can be validated (e.g., Maven compile checks) and iteratively improved. The project provides an IDE integration (VS Code extension/.vsix) for in-editor suggestions and a server-side stack to manage incidents, learned examples, and solution generation; Konveyor’s website and blog posts document the design, roadmap and early releases. Kai is in active community development with public releases and documentation. ([github.com](https://github.com/konveyor/kai))

Installation

Install via pip:

pip install git+https://github.com/konveyor/kai.git

Download the VS Code extension from the project's Releases page and install it in VS Code (recommended):

curl -L -o konveyor-kai.vsix "<release-asset-url-from-https://github.com/konveyor/kai/releases>"

code --install-extension ./konveyor-kai.vsix  # installs the VSCode extension from the downloaded .vsix

Key Features

• Retrieval-Augmented Generation (RAG) that augments LLM prompts with Konveyor static-analysis context.
• Learns from organization-specific "solved examples" to reuse prior migration fixes and reduce repeated LLM calls.
• VS Code extension (installable as a .vsix) surfaces suggested code changes inside the developer IDE.
• Model-agnostic: works with any LLM provider without requiring model fine-tuning.
• Agentic checks: can validate suggestions (e.g., Maven compile/dependency validation) before proposing automated edits.

Community

Kai is developed under the Konveyor community and actively discussed in Konveyor blogs, technical deep dives, and conference talks. The GitHub repository contains many commits, public issues and PRs, and a documented roadmap; Konveyor publishes release announcements and technical posts (including a dedicated 0.1.0 announcement and incident-storage deep dive). The project encourages contributions via the Konveyor contributor guides, mailing list and weekly community meetings. Users evaluating Kai should expect an early-stage, community-driven project (IDE-focused, prototype→release cadence) and can join Konveyor’s community channels to report issues or request features. ([konveyor.io](https://konveyor.io/blog/2025/kai-release-announcement/?utm_source=openai))

Key Information

• Category: Developer Tools
• Type: AI Developer Tools Tool