Data

Data in MadMax

The three kinds of durable data — stores, AI memory, and knowledge bases — what each is for and when to reach for which.

Workflows pass payloads step to step, but payloads die with the run. For data that outlives a run, MadMax has three purpose-built homes, all managed in Settings → data:

what it holds written by read by reach for it when
Data stores structured rows with a schema, keyed save to store steps get from store, the REST API workflows produce/consume records: results, caches, work queues
AI memory conversation turns, per session the AI agent automatically the same agent, next run an agent should remember prior exchanges ("as I said yesterday…")
Knowledge bases your documents, chunked + embedded you, by uploading agents, by semantic retrieval an agent should answer from your documents

The shorthand:

  • Stores are tables. Deterministic reads and writes, schema enforced, external API. If you'd reach for a spreadsheet or a database table, it's a store.
  • Memory is a chat log. The agent recalls the last N turns of a conversation, scoped by a session key. If the requirement sounds like "remember what this user said", it's memory.
  • Knowledge is a library. Documents in, relevant excerpts out at question time. If the requirement sounds like "answer based on our docs/policies/manuals", it's a knowledge base.

They compose: a support agent might retrieve the refund policy (knowledge), recall this customer's previous complaint (memory), and look up their order (store) — in one step.