Kaizen
Autonomous Software Modernization and Quality Engineering for Legacy Systems.
Accelerate legacy code modernization and rapid prototyping with AI-driven architectural slingshots.
CodeSlinger is a next-generation AI-augmented development environment designed to bridge the gap between architectural design and production-ready code. Built on a proprietary context-injection engine, CodeSlinger specializes in 'slingshotting'—the process of rapidly converting high-level natural language system designs into deeply nested, multi-file codebases. Unlike standard completion tools, CodeSlinger leverages a localized RAG (Retrieval-Augmented Generation) system that indexes entire repositories to maintain strict adherence to existing design patterns and security protocols. In the 2026 market, it positions itself as the premier tool for 'Technical Debt Remediation,' offering automated pathways to migrate legacy monoliths into microservices. Its architecture is LLM-agnostic, allowing enterprise users to toggle between Claude 4, GPT-5, and localized Llama-4 models depending on data sensitivity and performance requirements. The platform provides a seamless bridge between the IDE and CI/CD pipelines, ensuring that AI-generated code is not just syntactically correct, but also compliant with organizational linting, testing, and security standards through its integrated 'Guardian' agent.
Uses recursive prompting to generate complete multi-file directory structures from a single prompt.
Autonomous Software Modernization and Quality Engineering for Legacy Systems.
Bridge the gap between natural language and complex database architecture with AI-driven query synthesis.
Add AI-powered chat and semantic search to your documentation in minutes.
Automated Technical Documentation and AI-Powered SDK Generation from Source Code
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Analyzes monolithic codebases to identify logical boundaries for microservice extraction.
A real-time linting and security engine that runs static analysis on AI-generated code.
Locally indexes documentation and source code to provide hyper-specific context to the LLM.
Allows multiple developers to see AI code generations in a shared terminal/editor session.
Automatically generates edge-case unit tests using property-based testing methodologies.
Toggle between different LLM providers mid-session without losing session state.
Manually updating deprecated libraries and syntax in a 10-year-old codebase.
Registry Updated:2/7/2026
A monolith is too large to maintain; logical modules need to be extracted.
Spending days setting up auth, DB schemas, and API routes.