Code Graph RAG vs Meetily: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Code Graph RAG and Meetily — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
C
Code Graph RAG
vitali87
Multi-language monorepo RAG: Tree-sitter parses your codebase into a Memgraph knowledge graph so you can query, edit, and refactor in plain English.
Key features
- 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.
Best for
- 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.
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Meetily
Zackriya Solutions
Meetily is a privacy-first, open-source AI meeting assistant that transcribes and summarizes meetings entirely on your local machine, no cloud required.
Key features
- 100% Local Processing: Captures, transcribes, and summarizes meetings entirely on the user's machine so no audio or transcripts leave the device.
- 4x Faster Live Transcription: Real-time transcription powered by Parakeet or Whisper backends, tuned in Rust for up to 4x speedups over baseline.
- Speaker Diarization: Identifies who said what during a meeting so summaries and action items are correctly attributed.
- Ollama-Powered Summaries: Uses locally-running LLMs via Ollama to generate meeting summaries, key points, and action items without any cloud calls.
- Cross-Platform Desktop App: Ships as a native app for macOS and Windows, distributed through GitHub releases under an MIT license.
- Meetily PRO Upgrade: Optional paid tier for teams that need enhanced accuracy, advanced exports, custom summary workflows, and team-ready features.
Best for
- Enterprise Meeting Notes: Capture and summarize sensitive internal meetings without sending recordings or transcripts to third-party clouds.
- Regulated Industries: Provide meeting intelligence for healthcare, legal, and finance teams that must keep customer data on-premises.
- Executive Discussions: Generate summaries and action items for confidential board or strategy meetings on the executive's own laptop.
- Remote Team Standups: Automatically transcribe and summarize daily standups with speaker attribution for async team members.
- Open-Source Deployments: Self-host meeting AI as part of an internal privacy-first stack, replacing SaaS meeting note takers.