Comparisons

Enzyme vs raw markdown / Obsidian search

Use raw search when you know the literal thing:

  • a person name;
  • a tag;
  • a date;
  • a filename;
  • a quoted phrase;
  • a wikilink.

Use Enzyme when the useful question does not have one obvious keyword:

  • “What should I remember before the next meeting?”
  • “Where did this project change direction?”
  • “What older notes should inform this decision?”
  • “What commitments are still open?”

Search finds matches. Enzyme should return source-grounded context.

Enzyme vs RAG / vector DB over notes

A vector index retrieves semantically similar passages, which helps for broad passage search.

But Enzyme is architected differently:

workspace handles + prose
→ catalysts generated from entities and timelines
→ precomputed catalyst/document similarities
→ source files and excerpts for the agent

Use RAG/vector search when you want plain semantic retrieval over unstructured docs.

Use Enzyme when the workspace has visible structure — projects, folders, tags, links, dates, people, decisions — and the agent needs to prep from context across that structure.

Enzyme vs managed memory APIs

Managed memory APIs are useful when you are building an app and need a hosted backend for user memories, tenant scoping, SDK calls, dashboards, or production memory operations.

Enzyme’s local CLI is different:

  • memory starts from the user’s markdown workspace;
  • the source of truth remains ordinary files;
  • retrieval returns source files/excerpts;
  • writeback is conservative markdown;
  • setup assesses workspace indexability.

You might need a managed memory API if you need hosted app memory infrastructure. Use Enzyme if you expect your agent’s workspace to primarily operate in markdown.

Enzyme vs coding-agent memory tools

Some coding-agent memory tools capture conversations, summarize sessions, or maintain a memory database across tools.

Enzyme’s wedge is markdown-first:

  • project notes and decisions already exist;
  • meeting captures already exist;
  • agent observations can be written as source-linked markdown;
  • the next agent session can retrieve from those artifacts.

Use conversation-memory tools when the main source of truth is chat history. Use Enzyme when the main source of truth is a workspace you can inspect, edit, and version.

Enzyme vs larger context windows

A larger context window helps when you can afford to stuff more files into the prompt.

It does not decide which old notes matter, which project commitments remain open, or which files belong together despite not sharing vocabulary.

Enzyme is a routing layer before context. It helps the agent choose what to read and cite.

Choose something else if

  • You only need exact search.
  • Your workspace has too little prose or too few handles.
  • You need a managed hosted memory backend first.
  • You need enterprise team permissions, SSO, on-prem, or compliance guarantees before local experimentation.
  • You expect every stage, including catalyst generation, to be local without configuring a local provider.

Choose Enzyme if

  • Your markdown workspace already contains the trail.
  • You want agents to cite source files.
  • You want memory to stay inspectable and correctable.
  • You want setup to assess what is indexable instead of imposing a hidden schema.
  • You want cross-session continuity from artifacts, not generic chat summaries.