100+

File formats
searched instantly

Zero

Pre-indexing
required

5

Integration surfaces
MCP · REST · WS · CLI · Web

Key Features

An agentic search engine that goes beyond traditional RAG — embedding-free, self-evolving, and token-efficient.

Embedding-Free Retrieval

Work directly with raw data. No vector database, no pre-indexing, no ETL pipeline. Just drop your files and search immediately.

Self-Evolving Knowledge

Knowledge clusters compound with every search. The system learns and improves over time, delivering faster and richer results.

Monte Carlo Evidence Sampling

Strategically sample documents using exploration-exploitation methods. Extract precise evidence without reading entire files.

ReAct Agent Fallback

When standard retrieval falls short, an autonomous ReAct agent iteratively explores alternative strategies until answers are found.

Multi-Surface Integration

MCP protocol for AI-to-AI communication, REST API, WebSocket real-time chat, CLI, and a modern Web UI — all built in.

Token-Efficient Design

LLM inference triggered only when necessary. Monte Carlo sampling and knowledge reuse minimize costs while maximizing intelligence.

Start Searching with Sirchmunk

Drop your files and search instantly — no vector database, no pre-indexing, no complex setup. Get self-evolving intelligence from your raw data in real time.
Quick Start Guide