Kaizen
Autonomous Software Modernization and Quality Engineering for Legacy Systems.

Semantic code search and AI-driven navigation for massive, complex codebases.
Bloop is a high-performance code search engine designed for the era of Large Language Models, leveraging a technical stack centered on Rust and vector-based indexing. Unlike standard grep-based search tools, Bloop combines traditional keyword matching (BM25) with semantic vector search via Qdrant to understand the intent behind developer queries. Its architecture is optimized for local-first privacy, allowing developers to index entire GitHub or local repositories and interact with them using natural language. In the 2026 market landscape, Bloop has positioned itself as the critical 'Context Layer' for engineering teams, solving the 'Stale Knowledge' problem by providing real-time, symbol-aware navigation and AI agents that can traverse multi-repository dependencies. By utilizing tree-sitter for precise syntax parsing, Bloop offers 'Jump to Definition' and 'Find References' capabilities that are significantly more accurate than standard LLM hallucinations. It serves as a bridge between raw source code and the high-level reasoning required for large-scale refactors, security audits, and rapid developer onboarding in distributed systems.
Combines BM25 keyword matching with dense vector embeddings for 99.9% search recall accuracy.
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.
Uses incremental parsing to build a global symbol map of the codebase.
Indexes and stores vector data on the user's machine to ensure data privacy.
Maintains a unified index across multiple microservices to trace inter-service calls.
Real-time generation of code explanations with citations linking to source lines.
A domain-specific language for filtering search results by path, extension, and date.
AI agents that propose file changes across the entire indexed repository structure.
New hires spend weeks understanding how different modules interact in a 1M+ line codebase.
Registry Updated:2/7/2026
A zero-day is found in a library; need to find every vulnerable implementation pattern.
Upgrading a major framework requires changing syntax across hundreds of files.