Memory observability & monitoring
5 systems in the memory observability & monitoring category of the AI Agent Infrastructure Landscape, grouped by maturity tier.
Tier 1 — battle-tested (3)
- Galileo (galileo.ai) (now Splunk Agent Observability) Real-time intent / belief drift detection
Acquired by Cisco (announced 2026-04-09, closed by 2026-05); now Splunk Agent Observability. Treats memory as first-class in multi-agent tracing. Luna-2 SLMs (3B / 8B) scan every interaction for intent drift and belief drift; 20+ checks …
- Langfuse Memory ops as named spans + Agent Graphs
Acquired by ClickHouse (2026-01-16); product and MIT-licensed repo continue under the Langfuse name. Memory module reads/writes captured as named spans. Trace Log View concatenates every agent step including memory ops. Agent Graphs (GA …
- LangSmith Memory mutations as distinct span types
Memory reads, vector DB retrievals, state changes are distinct span types in traces. RAG eval separates retrieval quality (context precision) from generation quality (faithfulness). Dataset versioning guards against eval drift.
Tier 2 — production-ready (2)
- AgentOps Operational metrics for agent memory
When Mem0 is connected, gains Memory Operation Timeline, Search Analytics, Memory Growth tracking, Error Tracking per memory call. Standalone, records context at each step but doesn't analyse memory quality.
- Ratine Offline scanner — memory poisoning detector
Only tool found that scans the persistent memory layer on disk rather than runtime tracing. Detects injected instructions, obfuscated payloads (zero-width Unicode, base64, homoglyphs, hex), C2-pattern URLs, credential leakage. ratine dif…