LangSmith
Observability and evaluation platform for AI applications
You are leaving botconomy for the provider’s website. Link verified 9/21/2026.
What this product helps you do
LangSmith combines framework-agnostic tracing with production monitoring, offline and online evaluation, datasets, dashboards, alerts, and human review. Teams can inspect an agent's steps, compare versions against curated datasets, score live traffic, and turn production traces into evidence for the next development cycle.
Problems it solves
- Agent failures are difficult to reconstruct from final outputs alone
- Teams need repeatable quality checks before changing prompts or models
- Production quality, latency, and cost need ongoing monitoring
- Expert feedback and production traces need to feed future evaluations
LangSmith is LangChain's observability and evaluation platform for LLM applications and agents. Its tracing tools record model calls, tool activity, timing, cost, and other run data so teams can investigate failures and monitor behavior across supported frameworks and providers.
Evaluation workflows cover curated offline datasets, production scoring, LLM-as-judge and code-based evaluators, annotation queues, and prompt comparison. A free developer plan supports initial use, while paid and enterprise plans expand seats, usage, deployment, hosting, and administration.
Information
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LangSmith
Observability and evaluation platform for AI applications
LangSmith is LangChain's observability and evaluation platform for LLM applications and agents. Its tracing tools record model calls, tool activity, timing, cost, and other run data so teams can investigate failures and monitor behavior across supported frameworks and providers.
Evaluation workflows cover curated offline datasets, production scoring, LLM-as-judge and code-based evaluators, annotation queues, and prompt comparison. A free developer plan supports initial use, while paid and enterprise plans expand seats, usage, deployment, hosting, and administration.
What this product helps you do
LangSmith combines framework-agnostic tracing with production monitoring, offline and online evaluation, datasets, dashboards, alerts, and human review. Teams can inspect an agent's steps, compare versions against curated datasets, score live traffic, and turn production traces into evidence for the next development cycle.
Problems it solves
- Agent failures are difficult to reconstruct from final outputs alone
- Teams need repeatable quality checks before changing prompts or models
- Production quality, latency, and cost need ongoing monitoring
- Expert feedback and production traces need to feed future evaluations
Information
You are leaving botconomy for the provider’s website. Link verified 9/21/2026.
Related AI products
Limina
Limina, formerly Private AI, detects and transforms PII, PHI, PCI, and confidential company information across text, documents, images, and audio, with API, private-cloud, and on-premises deployment options.
Weaviate
Weaviate stores data objects and vector embeddings for semantic and hybrid search, retrieval-augmented generation, and agent workflows, with open-source self-hosting and managed cloud plans.
Microsoft Power Platform
Microsoft Power Platform combines Power BI, Power Apps, Power Automate, Power Pages, and Copilot Studio for low-code analytics, application development, process automation, websites, and agents.