Code Graph RAG vs Henji: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of Code Graph RAG and Henji — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

Code Graph RAG

vitali87

Freemium

Multi-language monorepo RAG: Tree-sitter parses your codebase into a Memgraph knowledge graph so you can query, edit, and refactor in plain English.

Multi-Language Graph Ingest: Tree-sitter parses Python, TypeScript, TSX, JavaScript, Rust, Go, Java, C, C++, C#, PHP, Lua, and Dart into a single language-agnostic Memgraph schema.
Natural-Language Cypher: The interactive CLI turns plain-English questions into Cypher queries and answers grounded in the real code structure, not vector-only guesses.
AST-Based Surgical Editing: The agent edits code through structural patches with a diff preview before any change is applied.
Structural Search & Replace: ast-grep is exposed as an agent tool, so you match and rewrite by AST pattern across the whole codebase instead of regex.
Pluggable ast-grep Tier: Add a new language from a single YAML pattern file — Ruby was added this way with Module/Function/Class nodes plus import edges.
Data-Flow Tracing: FLOWS_TO taint edges follow values through assignments, function calls, and I/O sinks across C, Java, C#, and Go.
Dead-Code Detection: Walk call and reference edges from entry points to find functions and modules nothing reaches.
Shared Graph Across Projects: Index many repos into one shared graph and query across them; a `clean` subcommand resets from scratch with confirmation.

Monorepo Q&A: Ask 'where is refund logic in this monorepo?' and get grounded answers from a graph of the real code, not stale docs.
AI-Assisted Refactoring: Rename or restructure APIs across languages with AST patches and a diff preview before commit.
Cross-Language Data-Flow Audits: Trace a value through assignments and function calls to see where sensitive data ends up.
Dead-Code Cleanup: Find unreachable functions and modules by walking call edges from entry points.
Codebase Onboarding: Give a new engineer or agent a queryable graph they can explore in natural language.
Structural Migrations: Use ast-grep to rewrite deprecated patterns (imports, error handling, config lookups) across a polyglot codebase.

Freemium

Mac app that drafts chat and email replies in your own voice across Slack, LINE, Gmail, and Messages.

Voice Matching: Learns your usual tone and phrasing over time so replies read as you-ish rather than AI-ish.
Tone Modes: Switch between Polite, Casual, Team, and Friends styles so each reply fits the relationship and channel.
Multi-Channel Coverage: Works across Slack, LINE, Gmail, and Messages so chat and email replies are handled in one place.
Scribble-to-Reply: Type a short note or intent and Henji expands it into a complete, context-aware message.
Multilingual: Supports multiple languages including English and Japanese for replies.

Faster Messaging: Knocking out quick chat and email replies during a busy day without sounding robotic.
Difficult Replies: Politely declining requests or negotiating deadlines while keeping the tone warm.
Team Communication: Keeping internal Slack threads fast and to the point with a team-appropriate tone.
Cross-Language Correspondence: Drafting replies in English or Japanese for international contacts.