If you’ve spent enough time working in massive enterprise codebases, you know the drill.

You pick up a ticket for a “simple” bug fix. But as you start tracing the logic, you quickly get tangled in a web of method calls, dependency injections, and data mutations. A 20-minute task spirals into hours of archaeology just to safely write a few lines of code.

Today, AI Agents promise to make this faster. They ingest your files into their context window and try to reason about your architecture. But have you ever watched an agent hallucinate a function or struggle to understand an external dependency? That happens because standard agents are flying blind. They treat code like flat text. They don’t explicitly know how classes and methods connect across your ecosystem.

Code Graphs solve this. And Decypher is a deterministic graph built from the ground up for the Agent-Native software engineering era.

Introducing Decypher

LLMs don't have a reasoning problem; they have a context problem. Give an agent flat text, and it guesses. Give it a deterministic code graph, and it executes flawlessly.

Decypher is the infrastructure layer that powers Agent-Native software engineering. It treats your codebase as a navigable map, constructing deterministic nodes and relationship edges between components so AI agents can traverse your architecture with absolute precision.

We built Decypher from the ground up specifically for autonomous environments. It doesn’t just understand the superficial structure of your code—it goes deep. Decypher maps out classes, methods, data flows, and control flows across your entire project and its external dependencies. All of this architectural data is then made instantly queryable in near real-time.

Decypher plugs directly into your AI agents through a native Model Context Protocol (MCP) interface, exposing 40+ specialized tools. This enables your agents to go far beyond basic text retrieval. They can precisely track inter-procedural data flows, identify variable sinks, and map request lifecycles. These are capabilities that are completely unmatched in the market today.

We have been using Decypher internally for the past few weeks to drive agentic interactions—from autonomously triaging complex bugs to identifying AppSec vulnerabilities across sprawling repositories. It has been a game-changing experience for our internal agents, and we are confident it will be the missing link for yours, too.

Today, we are officially making the Decypher Beta for JVM available to the public.

Head over to the Downloads page to give it a try. We are building this for the community, so we are always open to feedback. If you find a bug, have a feature request, or just want to talk about the future of code graphs, drop a note to saurabh [at] neuvem [dot] io.