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Solutions · AI builders

The substrate under your AI product.

Whether you’re shipping an AI feature or running a data pipeline, you need the same four things: memory that persists, a database, compute that scales out, and files your steps can share. sys9 gives you each as an atomic service — compose them, don’t assemble a stack.

the shape

Shard the work, share the memory.

Fork compute for the parallel parts, read and write a real database, recall one memory across every agent, and retrieve context semantically — all from the terminal or an agent skill.

a pipeline, composed

Parallel where it pays. Persistent where it counts.

mem9 keeps one memory across every agent and session, so context isn’t re-derived on each run. db9 holds the structured state. run9 forks the heavy stages out to a hundred sandboxes. drive9 carries the files between them.

one memory, many agents branch db + data + files 100 parallel forks semantic retrieval
terminal
run9 fork pipeline --as batch-7 --shards 50
  ✓ 50 sandboxes, sub-second start

db9 query "select id from documents limit 1000"
  ✓ 1000 rows · serverless Postgres

mem9 recall --key user-42
  ✓ one memory, across every agent

drive9 fs grep "Q3 pricing" /
  ✓ vector + BM25, in parallel
why build here

Composable, agent-native, no lock-in.

Atomic & composable

Each service does one job. Start with one, add the rest when you need them — there’s no bundle to buy or framework to adopt.

Use-first, claim-later

No signup to start. Hand an agent the skill and it provisions what it needs; attach an account when you’re ready to keep it.

Works with your agents

mem9 plugs into the runtimes you already use, so memory and retrieval aren’t tied to one agent framework.

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use-first, claim-later

Build your AI product on composable parts.

Hand an agent the sys9 skill, or install the CLI and start with the one service you need today.