How ServiceNow uses LangSmith to get visibility into its customer success agents
Blog post from LangChain
ServiceNow is enhancing its sales and customer success operations by developing an intelligent multi-agent system using LangChain's LangSmith and LangGraph tools, which address the challenges of agent orchestration and observability. This system orchestrates the entire customer journey, from lead identification to post-sales adoption and expansion, by coordinating complex workflows that were previously fragmented. ServiceNow's approach involves using a supervisor agent for orchestration and specialized subagents for specific tasks, activated by customer signals and lifecycle stages. LangGraph provides the necessary tools for sophisticated multi-agent coordination, enabling a modular and efficient development process, while LangSmith offers detailed tracing and evaluation capabilities to improve agent performance. The evaluation framework includes custom metrics tailored to each agent's tasks, leveraging LLM-as-a-judge evaluators and ensuring regression prevention. Currently in testing, ServiceNow plans to integrate real user data and utilize new multi-turn evaluation features for more comprehensive assessments of agent performance across the entire customer interaction.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| Multi-agent systems | 6 | 338 | 121 | 62 | +27% |
| Observability | 6 | 3,012 | 601 | 171 | +15% |
| Harness engineering | 3 | 67 | 46 | 28 | +22% |
| LLM | 2 | 5,048 | 855 | 225 | +5% |
| MCP | 2 | 5,085 | 420 | 153 | -2% |
| RAG | 1 | 1,167 | 195 | 86 | +2% |
Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.