Automate with AI
Automate LangSmith with AI Agents.
Automate AI app evaluation and observability with LangSmith and AI workers. Use Toolhouse to monitor runs, surface failures, and keep LLM workflows improving over time.
Top LangSmith automation use cases
Toolhouse AI workers can use LangSmith to monitor how LLM-powered workflows perform across support, operations, and customer-facing automations. Workers can watch trace activity, flag quality drops, and identify patterns that suggest prompt or workflow issues. This helps teams catch performance problems before they affect more users. It turns AI monitoring into a repeatable operational workflow instead of a manual review task.
When AI workflows fail, teams often waste time digging through logs and scattered context. With LangSmith in the workflow, AI workers can summarize failed traces, highlight likely causes, and route the issue to the right operator or builder. That speeds up troubleshooting and reduces downtime for AI-powered support, content, and internal automation systems. Faster investigation means teams can improve reliability without adding more manual overhead.
Prompt testing and evaluation are critical, but they are often inconsistent across teams. Toolhouse can use LangSmith to automate evaluation workflows that compare prompt versions, track outputs, and surface regressions that need review. AI workers can help standardize how teams improve customer service bots, lead generation assistants, and workflow automation agents. This creates a more reliable process for improving AI quality over time.
Non-technical leaders still need visibility into whether AI workers are helping or hurting business operations. AI workers can turn LangSmith activity into clear reporting on trace volume, failure trends, response quality, and workflow health. That makes it easier for support, operations, and product teams to understand where automation is performing well and where it needs attention. Better reporting helps teams justify AI investments and prioritize improvements.
Production AI workflows generate signals that matter only if someone acts on them quickly. Toolhouse AI workers can use LangSmith to detect risky patterns, route incidents into internal workflows, and trigger follow-up tasks when quality or reliability changes. This is especially useful for businesses running AI-powered support, outbound automation, or content generation at scale. Teams can respond faster and keep important workflows stable as usage grows.
Testimonials
What our customers say
7,000+ teams · 1,000+ integrations · Start for free
Marcos Ocón
COO @ Develative (Developer Agency)
"We built in record time what would have taken weeks otherwise!
I can honestly say that without Toolhouse, our team would have been spending much MUCH more time delivering AI features in the products we're building"
Engineering
Andrew Njoo
Founder @ Stack2Sale
I built an agent that qualifies my leads and books calls automatically. No developer, no agency. It paid for itself in the first week.
Marketing
Kristian Freeman
Our team of 12 was drowning in repetitive tasks. We described what we needed and the agent just worked. We didn't write a single line of code.
Operations
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Common questions about LangSmith automation with AI workers.
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