How It Reduces AI Costs

The Problem

AI coding tools (Copilot, Cursor, Claude Code, etc.) are powerful but expensive. Every time they work on your code, they need to find the relevant files. Without an index, they do it the hard way:

Run grep or find across your project
Read file after file hoping to find the right one
Repeat until they locate the code they need

Each step burns LLM tokens. On a large codebase, a single task can consume thousands of tokens just on navigation — before the AI even starts thinking.

The Solution

GrepAI pre-indexes your codebase semantically. AI agents query the index and get precise results on the first try.

Without GrepAI (typical AI agent workflow):
  grep "auth" → 500 files scanned      → 2,000 tokens
  read file A → not relevant            → 800 tokens
  read file B → not relevant            → 1,200 tokens
  read file C → found it                → 600 tokens
  Total: ~4,600 tokens to locate one function

With GrepAI:
  grepai search "authentication flow"   → 3 results, 400 tokens
  Total: ~400 tokens — 91% reduction

How It Works

GrepAI watches your project files and maintains a semantic index in the background. When an AI agent needs to find code, it queries GrepAI instead of scanning files.

Natural language search — “find the login logic” works
Call graph tracing — “what calls this function?” in one query
Compact output mode — sends only essential context to the LLM, not entire files
Auto-updated — every file save refreshes the index

You don’t configure anything. GrepAI starts indexing when you open your project.

Real Impact

Codebase Size	Without GrepAI (tokens/task)	With GrepAI (tokens/task)	Savings
Small (~100 files)	~3,000	~500	83%
Medium (~1,000 files)	~8,000	~600	92%
Large (~10,000 files)	~15,000+	~800	95%

The larger your project, the more you save.

Works With Any AI Tool

GrepAI exposes its intelligence via the MCP protocol (Model Context Protocol). Any AI tool that supports MCP can use it automatically. For tools that don’t, agents can call grepai search from the terminal.

At team scale, AI costs compound fast. → Aether Platform for Teams