sales_ops · saas · workflow

Unify builds account qualification agents powered by LangGraph and LangSmith

Go-to-market teams needed a systematic way to research and qualify prospect accounts based on custom criteria, a task requiring web search, website visits, and multi-source synthesis that was not yet automated.

How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Account qualification request
Given a company and a set of questions and criteria, the agent begins a qualification research run.
Tools used
LangGraphLangSmitho1-previewGPT-4o3.5 Sonnet
Outcome

Unify evolved to a plan-reflect-tools architecture with parallelized tool calls for speed and a real-time step-by-step UI showing the agent's decision-making, with LangSmith enabling experiment comparison across hundreds of examples with minimal in-house ML infrastructure.

What failed first

The initial agent version produced inconsistent results and made it difficult to analyze reasoning. The early UX showed only a spinner during agent runs, which became painful as runtimes grew.

Results
Time savedup to 30-45 seconds
Volumeone of the biggest speed boosts
Source

https://blog.langchain.dev/unify-launches-agents-for-account-qualification-using-langgraph-and-langsmith/

How we source this →

Grounding & classification
Source type: technical build writeup
22 fields verified against source quotes.
agentic workflowai agentdata extractionbuilder submittedfailure mode describednamed customerproduction runtime claimedtools describedworkflow describedsoftwarecycle time reductiontechnical build writeuplead processingsales opsagentic task execution