SanctifAI builds Human-AI collaboration platform using n8n
SanctifAI needed a horizontally scalable, distributed, and composable way to integrate human workers into AI agent workflows without building or maintaining a custom in-house codebase.
SanctifAI evaluated LangChain tools but found they lacked the flexibility needed to incorporate the custom logic required by the platform.
n8n became the core of SanctifAI's products, enabling access to 400 diverse and highly specialized workforces.
The first n8n workflow was built in little over two hours — three times faster than writing Python controls for LangChain — and product managers can now build and test directly without engineering bottlenecks.
Frequently asked questions
What did this team achieve with this AI workflow?
n8n became the core of SanctifAI's products, enabling access to 400 diverse and highly specialized workforces.
What tools did this team use?
n8n.
What results were reported?
Time to first workflow: little over two hours; build speed vs LangChain Python controls: three times faster; Workforce providers accessible: 400; Development efficiency: dramatic efficiencies in both prototyping and production workloads (source-reported, not independently verified).
What failed first in this deployment?
SanctifAI evaluated LangChain tools but found they lacked the flexibility needed to incorporate the custom logic required by the platform.
How is this back office ops AI workflow structured?
Customer creates workflow → HaaM/HaaT configured via n8n → Tasks published to Worker Portal → Human workers complete tasks → Response streamed back to n8n.