Your agent produces an output—a research report, a dataset, a code patch. Now you have to store it durably, index it for retrieval, handle duplicates when the agent retries, and generate a secure link for human review.

That's weeks of engineering spent on S3 buckets and Postgres tables instead of your core product. It's infrastructure plumbing, and every AI team is rebuilding it from scratch.

Seamless multi-agent handoffs.

Complex AI workflows require passing context and files between sub-agents. Artifacta replaces fragile /tmp directories and shared NFS mounts with a deterministic, agent-native API.

Agent A pushes an output and receives an immutable ID. Agent B pulls it by ID or queries the session metadata. No path conventions, no race conditions, no timing hacks. Just a clean, zero-config handoff.

› pip install artifacta-cli// CLI + Python SDK in one package

› artifacta push <file> --session ses_run1// Store artifact, deduplicate, tag to session

› artifacta pull <artifact_id>// Retrieve by ID across agents and processes

› artifacta ls --session ses_run1 --agent eval// Query what a specific agent produced in a run