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LangSmith vs Moda
Short answer: Pick LangSmith if you want LLM app observability; pick Moda if you want production monitoring for AI agents. LangSmith has a free plan, paid from $39/month per user.
LangSmithTracing, evals and monitoring for LLM apps
ModaProduction monitoring and evals for AI agentsWhich to pick
Pick LangSmith if you want…
- LLM app observability
- Integrations with OpenAI SDK, Anthropic SDK or Vercel AI SDK (on LangSmith's list, not Moda's)
Pick Moda if you want…
- Production monitoring for AI agents
- Integrations with Slack, Linear or email (on Moda's list, not LangSmith's)
Side by side
- What it is
- LangSmith:LangSmith provides tracing, monitoring, and evaluation for LLM applications and AI agents.
- Moda:Moda monitors AI agents in production, detects mistakes, groups problems and lets you replay changes as evals.
- Best for
- LangSmith:LLM app observability
- Moda:Production monitoring for AI agents
- Who it’s for
- LangSmith:Developers and teams building LLM-based agents and applications.
- Moda:Teams running AI agents in production who need error detection and remediation.
- Pricing
- LangSmith:Freemium
- Moda:Contact sales
- Starting price
- LangSmith:$39/month per user (Plus)
- Moda:—
- Free plan or trial
- LangSmith:Free plan (Developer)
- Moda:—
- Plans
- LangSmith:Developer $0 per seat per month · Plus $39 per seat per month
- Moda:—
- Works with
- LangSmith:OpenAI SDK, Anthropic SDK, Vercel AI SDK, LlamaIndex, OpenTelemetry, LangChain
- Moda:Slack, Linear, email
LangSmith features
- Tracing SDKs. Native tracing for popular agent frameworks via Python, TypeScript, Go, and Java SDKs.
- Real-time Monitoring. Dashboards show latency, cost, token usage and support alerts via webhooks or PagerDuty.
- Insights & Clustering. Unsupervised topic clustering and error-analysis templates automatically surface usage patterns.
- SmithDB Query Engine. Purpose-built database for fast, random-access queries, full-text search and JSON-path filtering.
- Self-hosted Options. Managed cloud, BYOC, or fully self-hosted deployments keep data inside your VPC.
- Online Eval as LLM-as-Judge. Run code and response evaluations in real time to score quality.
- Cost Tracking. Track token usage and LSUs, with pay-as-you-go pricing per trace volume.
- Alert Integrations. Webhook and PagerDuty alerts trigger on custom metric thresholds.
Moda features
- Trace Monitoring. Reads every production trace end-to-end and flags hidden failures like hallucinations and tool errors.
- Custom Signals. Define plain-language checks that generate alerts when agents misbehave.
- Alert Integrations. Send failure alerts to Slack, Linear or email.
- Problem Grouping. Aggregates similar failures into ranked problems based on affected users.
- Replay Testing. Re-run prompts, models or tool changes against failing traces to compare pass rate, latency and token usage.
- Metrics Dashboard. Shows signal rate, pass/fail stats, latency and token usage trends.
LangSmith vs Moda FAQ
What is the difference between LangSmith and Moda?+
Moda focuses on production monitoring and evals for AI agents, while LangSmith adds full tracing, SmithDB query engine and self-hosted deployment options.
Should I use LangSmith or Moda?+
Pick LangSmith if you want LLM app observability or integrations with OpenAI SDK, Anthropic SDK or Vercel AI SDK (on LangSmith's list, not Moda's). Pick Moda if you want production monitoring for AI agents or integrations with Slack, Linear or email (on Moda's list, not LangSmith's).
Is LangSmith or Moda free?+
LangSmith has a free plan (Developer); paid plans start at $39/month per user (Plus).
Do LangSmith and Moda integrate with the same tools?+
Their integration lists don't overlap: LangSmith lists OpenAI SDK, Anthropic SDK, Vercel AI SDK, LlamaIndex and 2 more; Moda lists Slack, Linear and email.
On DevHunt
Based on each tool's website and DevHunt data. Details may change; check the official sites.