LangSmith
https://www.langchain.com/langsmith
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.
At a glance
- Type
- Memory mutations as distinct span types
- Tier
- T1
- Created
- 2023 (LangSmith beta summer 2023; GA Feb 2024 with $25M Series A)
- Latest release
- not applicable — not OSS
- License
- not applicable — not OSS
- GitHub
- not applicable — no GitHub repo
- Pricing
- Developer: free (5K traces/mo); Plus: $39/seat/mo (10K traces); Enterprise: custom (SSO/SAML; dedicated support)
- Funding
- LangChain total ~$35M+ ($3M seed Benchmark 2023; $25M Series A Sequoia Feb 2024; $125M Oct 2025 unicorn round at $1…
Taxonomy
- storage
- relational
- retrieval
- exact-match
- persistence
- long-term
- update
- append-only
- unit
- episode
- governance
- auditable
- conflict
- n/a
When to use
Optimised for: memory operation tracing + drift / poisoning detection
Anti-fit: not for use cases that don't run agent workloads in production
Pros & cons
Pros
Best integration with the LangChain / LangGraph stack — debug memory + chain + agent in one trace; the de-facto trace tool for that ecosystem.
Cons
LangChain-shaped — works less well outside that ecosystem; closed SaaS.
Claims & capabilities
Free 5k traces/month Developer; Plus $39/mo; Enterprise custom. No automated drift / poisoning detection.
Technical surface
- API surface
- REST, SDK: Python, JS/TS
- Backend storage
- custom (LangChain-managed)
- Deployment
- SaaS cloud (US); Enterprise: dedicated tenant
- Embedding model
- not applicable — observability product
- Multi-tenancy
- namespace (workspace/project)
- MCP
- via LangChain MCP adapters
- A2A
- no data — searched langchain.com/langsmith, docs.smith.langchain.com, docs.smith.langchain.com/observability/concepts; A2A protocol not advertised (OTel-based traces, webhook automations)
- OpenTelemetry
- first-class — OTel ingestion + export
Compare LangSmith with…
Similar systems
Other memory observability & monitoring in the catalog, ranked by inbound references.
- AgentOps T2
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.
- Galileo (galileo.ai) T1
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 at sub-200ms latency. Catches when agent A's view of the world splits from teammate B's. OpenTelemetry-compatible.
- Langfuse T1
Memory module reads/writes captured as named spans. Trace Log View concatenates every agent step including memory ops. Agent Graphs (GA 2025) infer graph structure from observation nesting; session-level replay tracks how memory state evolves.
- Ratine T2
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 diff compares snapshots for belief drift.
Related systems
References (3)
- LangChain (framework) integrates with — Best integration with the LangChain / LangGraph stack — debug memory + chain + agent in one trace
- LangChain (framework) depends on at runtime — backend-storage cell: custom (LangChain-managed)
- LangGraph Persistence integrates with — de-facto trace tool for that ecosystem