AI-enhanced procurement and AP automation for mid-market spend control
Procurify operates a Python/Django monolith serving hundreds of mid-market customers managing over $30B USD in organizational spend. The engineering org is actively decomposing that monolith into modular services while simultaneously building agentic AI systems with RAG pipelines and LangChain—a dual architectural shift that explains the hiring deceleration (7 roles posted in 30 days across 51–200 headcount) and the explicit pain point of balancing technical debt against feature velocity. The stack reveals a mature ops foundation (Kubernetes, Terraform, AWS WAF, GuardDuty) paired with emerging AI capability, positioning the platform toward real-time, data-driven procurement intelligence.
Procurify is a procurement and accounts payable automation platform serving mid-market organizations. The product integrates the full procure-to-pay cycle—from purchase requests and approvals through invoicing and payment—with native budget management and real-time spend visibility. It connects to major ERP systems including NetSuite, Sage Intacct, Microsoft Dynamics 365, and QuickBooks Online. The company is headquartered in Vancouver, British Columbia, and operates with a lean sales organization (3 active sales roles) while maintaining a larger engineering team focused on backend scalability and architectural modernization. Current priorities include scaling the platform architecture, reducing performance bottlenecks, and implementing AI-powered features for customer implementation and workflow optimization.
Python, Django, TypeScript, React, AWS, Kubernetes, MySQL, and Terraform form the core stack. LangChain and pgvector power emerging AI capabilities; Databricks supports data processing.
Decomposing the Python/Django monolith into modular services, building agentic AI systems and RAG pipelines, scaling backend services, developing a new vendor portal, and improving workflow configuration for customers.
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