Looking for AI agents with permanent memory + token optimization as core architecture

I'm looking for AI agents that go beyond the current landscape of memory and token optimization. I'm aware of:

• Zeph doing memory-first with scoped sub-agent persistence (user/project/local MEMORY.md files)
• Caveman skill for token optimization (~8.5% output savings in real agentic work)
• RTK providing shell command compression and context management

What I'd really like is something more integrated:

Memory: Layered memory systems like ICM's dual approach (episodic "Memories" with decay + semantic "Memoirs" as permanent knowledge graphs) or Memori's Advanced Augmentation that structures unstructured dialogue into semantic triples + conversation summaries. Something that treats memory as a structuring problem, not just storage.

Token optimization: Built-in compact mode as a permanent configuration, not a skill I have to toggle. Something like the token-optimization stack that combines CBM + context-mode + RTK + Headroom + Caveman with enforcement hooks, but as a cohesive, always-on system.

The gap: Most agents treat memory and token efficiency as add-ons. I want something where they're baked into the architecture from the ground up—layered persistence (short-term working memory, long-term semantic graph) with aggressive context compression and retrieval planning that doesn't require manual intervention.

Is there anything out there that fits this? Or am I asking for a unicorn?