Kaizen
Autonomous Software Modernization and Quality Engineering for Legacy Systems.
Private, self-hosted AI coding infrastructure for high-security enterprise environments.
CodeAI Server, powered by the Refact.ai architecture, represents the 2026 standard for secure, autonomous software development lifecycles. Designed specifically for enterprises with stringent data residency requirements (SOC2, HIPAA, GDPR), it allows organizations to host their own AI inference engine on-premises or within a private cloud (VPC). The technical core utilizes the Triton Inference Server for high-performance model serving, supporting a variety of state-of-the-art open-source LLMs like Llama 3, StarCoder2, and Mistral. Unlike cloud-based competitors, CodeAI Server integrates a proprietary RAG (Retrieval-Augmented Generation) engine that indexes local codebases in real-time, providing context-aware suggestions without data ever leaving the internal network. The 2026 iteration features advanced fine-tuning capabilities, allowing teams to train models on their internal libraries and legacy code, significantly reducing technical debt. Its architecture is optimized for NVIDIA GPU clusters but includes quantization support for efficient operation on mid-range hardware, making it a versatile choice for both massive engineering departments and agile, security-conscious startups.
Vectorizes the entire local repository using embeddings to provide contextually relevant code suggestions.
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.
Allows the server to perform LoRA fine-tuning on your specific codebase overnight.
Dynamically switches between smaller models for speed and larger models for complex logic.
Filters and masks PII or sensitive keys before they reach the inference engine.
Distributes inference requests across a cluster of GPUs using load balancing.
Admin-defined templates for standardized unit testing or documentation styles.
Natural language search across the codebase using vector embeddings.
Safe refactoring of COBOL/Old Java code without cloud exposure.
Registry Updated:2/7/2026
New hires struggle to understand complex internal frameworks.
Inconsistent or missing documentation across 50+ repositories.