LangSmith vs Helicone

Detailed side-by-side comparison to help you choose the right tool

LangSmith

πŸ”΄Developer

AI Observability

LangSmith is LangChain’s LLM observability and evaluation platform for tracing, testing, monitoring, and improving AI agents.

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Starting Price

Free

Helicone

πŸ”΄Developer

AI observability

open-source LLM observability and gateway platform

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Starting Price

Free

Feature Comparison

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FeatureLangSmithHelicone
CategoryAI ObservabilityAI observability
Pricing Plans4 tiers4 tiers
Starting PriceFreeFree
Key Features
  • β€’ Workflow Runtime
  • β€’ Tool and API Connectivity
  • β€’ State and Context Handling
  • β€’ Proxy-Based Request Logging
  • β€’ Cost Analytics & Budget Alerts
  • β€’ Gateway-Level Caching

πŸ’‘ Our Take

Choose LangSmith if you need deep evaluation tooling, prompt versioning, and hierarchical agent traces tied to the LangChain ecosystem. Choose Helicone if you primarily need a lightweight proxy-based observability layer for OpenAI/Anthropic API calls with caching and rate limiting, and want simpler setup at a lower starting price.

LangSmith - Pros & Cons

Pros

  • βœ“Very strong fit for teams already building with LangChain or LangGraph because tracing, evals, prompts, and deployments sit in the same ecosystem.
  • βœ“The free Developer plan is useful for early projects because it includes up to 5k base traces per month rather than only a demo sandbox.
  • βœ“Supports both debugging workflows and production monitoring, so teams can use one system from prototype through release.
  • βœ“Enterprise deployment options include hybrid/self-hosted patterns for teams that cannot send sensitive traces to a hosted SaaS environment.
  • βœ“SDK coverage across Python, TypeScript, Go, and Java makes it workable outside a single framework choice.

Cons

  • βœ—The best experience is developer-oriented; product managers and analysts will usually need engineering help to instrument traces and evaluations well.
  • βœ—Costs can become usage-modeling work because seats, traces, Fleet runs, sandboxes, and model-provider charges are separate considerations.
  • βœ—It is naturally biased toward the LangChain ecosystem, which may be a drawback if your stack is built around a different observability standard.
  • βœ—The official /langsmith/pricing URL returned a 404 during this run, so pricing was verified from the alternate LangChain pricing page and should be rechecked before purchase.
  • βœ—Self-hosting, custom SSO/RBAC, and formal support SLA are Enterprise items rather than default features on the $39 Plus plan.

Helicone - Pros & Cons

Pros

  • βœ“Open-source positioning and one-line integration reduce adoption friction
  • βœ“Pricing is more transparent than many LLM observability tools
  • βœ“Combines observability and gateway controls in one product

Cons

  • βœ—Hobby plan limits retention to 7 days and ingestion to 10 logs/min
  • βœ—Advanced compliance and Slack support start at the $799/month Team tier
  • βœ—Teams needing deep eval workflows may still compare against Braintrust or Langfuse

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πŸ”’ Security & Compliance Comparison

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Security FeatureLangSmithHelicone
SOC2βœ… Yesβœ… Yes
GDPRβœ… Yesβœ… Yes
HIPAAβ€”βŒ No
SSOβœ… Yesβœ… Yes
Self-HostedπŸ”€ Hybridβœ… Yes
On-Premβœ… Yesβœ… Yes
RBACβœ… Yesβœ… Yes
Audit Logβœ… Yesβœ… Yes
Open Source❌ Noβœ… Yes
API Key Authβœ… Yesβœ… Yes
Encryption at Restβœ… Yesβœ… Yes
Encryption in Transitβœ… Yesβœ… Yes
Data ResidencyUS, EUUS, EU
Data Retentionconfigurableconfigurable
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