back_office_ops · realestate · workflow

Build.inc uses LangGraph multi-agent architecture to complete CRE land diligence in 75 minutes versus four weeks manually

Land diligence workflows for energy-intensive CRE projects (data centers, renewable energy) took over four weeks, consumed nearly half of the total project timeline, and cost developers millions of dollars. The fragmented US regulatory landscape and the need for deep specialist expertise made traditional software solutions inadequate.

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 · Land diligence request initiated
Real estate stakeholders hire the worker to research a piece of land to understand if it is suitable for a particular project.
Tools used
LangGraphLLMs
Outcome

Build.inc's first worker, Dougie, is now in production for CRE industry clients and completes land diligence in 75 minutes—what previously took humans over four weeks—with a depth and quality that human teams cannot match even over the course of several weeks.

What failed first

Traditional software could not handle the complexity and variability, fragmented data ecosystem, and high-stakes specialist requirements of CRE development workflows.

Results
Time saved75 minutes
Volumeover 25
Cost replacedcost developers millions of dollars
Running sincein production
Source

https://blog.langchain.dev/how-build-inc-used-langgraph-to-launch-a-multi-agent-architecture-for-automating-critical-cre-workflows-for-data-center-development/

How we source this →

Grounding & classification
Source type: technical build writeup
28 fields verified against source quotes.
agentic workflowai agentmulti agent workflowknowledge basefailure mode describedmetric backednamed customerproduction runtime claimedtools describedworkflow describedenergyreal estatecycle time reductionemployee productivitytechnical build writeupback office opsagentic task execution