Examples
Real-world scenarios and sample solutions built with Meko
Enhanced team efficiency and productivity
Knowledge handoff with context preserved
Agent B gets Agent A's reasoning, not just its final output. No lost context across agents.
Collective learning across runs
What worked, what didn't, and why — available on the next run when you save it.
Group/team policies and standards
Share a datapack across your team so every agent works from the same playbook.
Traceability, efficient conversation history, resumability and more
Auditable learning trail
Full chain-of-thought traceability for what agents learned and how it flowed — ready for EU AI Act compliance.
Conversation history with tiering
Recent history in-database for fast recall; older history auto-tiered to S3 to control costs.
Agent resumability
Persist full agent and sub-agent state in Meko so any run can be paused and resumed reliably.