LangSmith
LangSmith is an LLM observability and testing platform from LangChain, providing tracing, evaluation, and debugging tools for LLM applications.
Overview
Company: LangChain (San Francisco) Founded: 2022 Funding: $35M+ (Series A, Sequoia) Pricing: Free tier, Developer at $39/mo, Team at $500/mo
Why They’re Not a Direct Competitor
LangSmith is for debugging. Nomos is for compliance.
| LangSmith | Nomos Cloud | |
|---|---|---|
| User | ML engineer | Compliance officer, legal, exec |
| Question | ”Why did this fail?" | "Why was this allowed?” |
| Data model | Spans and traces | Decisions and authorizations |
| Output | Technical debugging UI | Human-readable audit trails |
The Core Difference
LangSmith helps engineers fix broken AI systems. Nomos helps enterprises prove their AI systems followed the rules.
A LangSmith user:
- Is debugging a failed LLM chain
- Needs to see which prompt caused the error
- Wants latency and cost breakdowns
- Is optimizing model performance
A Nomos user:
- Is preparing for a compliance audit
- Needs to show why an AI made a specific decision
- Wants tamper-evident records
- Is proving governance to regulators or executives
Complementary, Not Competitive
Many teams will use both:
- LangSmith in development and staging (debugging, evaluation)
- Nomos in production (audit trails, compliance)
The pitch: “LangSmith for debugging. Nomos for compliance. You need both.”
Framework Lock-In
LangSmith is tightly coupled to LangChain. Nomos is framework-agnostic—works with LangChain, AutoGPT, CrewAI, or custom agents.
Threat Level: Low
LangSmith could add compliance features, but it’s not their focus. They’re optimizing for developers building with LangChain, not enterprises proving compliance.