Why agent memory breaks in production

Most agent memory systems look solid in demos and quietly fall apart under production pressure.

The common reasons are straightforward: patterns get stored without strong evaluation, recall quality is not measured, and the system lacks governance for bad memories.

Engramia is designed around the opposite assumptions. Learning is explicit, recall is measurable, and every retrieval decision can be inspected, scored, and improved.